All Classes
| Class | Description |
|---|---|
| AblationExperimentExample |
A learning to rank experiment that performs ablation on the different variables.
|
| AbstractClassificationMetric<U> |
Implementation of the area under the receiver-operating characteristic curve
for link prediction.
|
| AbstractClusteringCoefficientReranker<U> |
Swap reranker that promotes a metric related to the global clustering coefficient of the network.
|
| AbstractCommunityDegreeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| AbstractCommunityEdgeGiniComplement<U> |
Swap reranker for promoting the balance in the distribution of the number of links
between pairs of communities.
|
| AbstractDataFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for filtering unnecessary data for simulations.
|
| AbstractDistribution<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Abstract class for defining a distribution of elements.
|
| AbstractExternalFeatureGlobalSimulationMetric<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Abstract class for representing global feature-based metrics which consider those features that the user already knows.
|
| AbstractExternalFeatureIndividualSimulationMetric<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Abstract class representing individual feature-based metrics which do not take into account features that the user already knows
(with already knows meaning that the user has the feature, in case of user features, or the user has an information piece containing
the feature, in case of information features).
|
| AbstractFastFiller<U,I> |
Abstract implementation of a fast filler.
|
| AbstractFastGraph<V> |
Fast implementation of a graph.
|
| AbstractFastGreedy<U> |
Abstract class for the implementation of Fast Greedy algorithm versions for optimizing modularity.
|
| AbstractFastMultiGraph<U> |
Fast implementation of a multi graph
|
| AbstractFastUpdateablePreferenceData<U,I> |
Abstract updateable fast preference data, implementing the FastUpdateablePreferenceData interface.
|
| AbstractFastUpdateableRecommender<U,I> |
Abstract (fast) updateable recommender.
|
| AbstractFeatureGlobalKLDivergence<U extends java.io.Serializable,I extends java.io.Serializable,F> |
This global metric computes the KL divergence of the priori distribution of the feature values over the whole set of information pieces,
and the frequency of receival of these parameters for the set of users.
|
| AbstractFeatureGlobalSimulationMetric<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class that represents a global metric that considers the existence of several features.
|
| AbstractFeatureIndividualSimulationMetric<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Class that represents an individual metric that considers the existence of several features.
|
| AbstractFeatureKLDivergence<U extends java.io.Serializable,I extends java.io.Serializable,P> |
This individual metric computes the KL divergence of the priori distribution of the parameter
values over the whole set of information pieces, and the frequency of receival of
these parameters for a single user.
|
| AbstractGlobalSimulationMetric<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Abstract class for representing global simulation metrics.
|
| AbstractHeuristicNeighborOverlapReranker<U> |
Swap reranker that modifies the rankings according to the average embeddedness of the network.
|
| AbstractHittingTime<U> |
Abstract version of the hitting time algorithm.
|
| AbstractIndex<C> |
Abstract implementation of an index.
|
| AbstractIndexBuilder<C> |
Abstract implementation of an index builder.
|
| AbstractIndividualContentIndex<C,U> |
Abstract implementation of a content index.
|
| AbstractIndividualContentIndexBuilder<C,U> |
Abstract implementation of an individual content index.
|
| AbstractIndividualSampler<U> |
Abstract implementation of the IndividualSampler interface.
|
| AbstractIndividualSimulationMetric<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Abstract class for representing global simulation metrics.
|
| AbstractLinkPredictor<U> |
Abstract definition of a link prediction algorithm.
|
| AbstractNeighborOverlapReranker<U> |
Class that tries to maximize the average embededness of the graph.
|
| AbstractPairMetric<U> |
Abstract implementation of a pair metric.
|
| AbstractSearchEngine |
Abstract implementation of a search engine.
|
| AbstractSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Abstract implementation of a selection mechanism.
|
| Accuracy<U> |
Implementation of the accuracy metric for link prediction.
|
| AccuracyConfigurator<U,F> |
Grid search generator for the accuracy of the link prediction method.
|
| AdamicAdar<U> |
Recommender that uses the Adamic-Adar coefficient of the neighbours.
|
| AdamicAdarGridSearch<U> |
Grid search generator for Adamic-Adar algorithm.
|
| AdamicSimilarity |
Similarity based on the Adamic-Adar link prediction approach.
|
| Adapters |
Methods for filtering the users and edges from a graph.
|
| AggregateEdgeMetric<U> |
Graph metric computed as the aggregation of an edge metric over the edges in the network.
|
| AggregateIndividualCommMetric<U> |
Aggregate individual community metric.
|
| AggregatePairMetric<U> |
Graph metric computed as the aggregation of an pair metric over the pairs of users in the network.
|
| AggregateVertexMetric<U> |
Graph metric computed as the aggregation of an vertex metric over the nodes in the network.
|
| AlgorithmConfigurationsReader |
Class for reading contact recommendation / link prediction algorithms.
|
| AlgorithmGridReader |
Class for reading contact recommendation / link prediction algorithms.
|
| AlgorithmGridSearch<U> |
Class for performing the grid search for a given algorithm.
|
| AlgorithmGridSelector<U> |
Class that translates from a grid to the different contact recommendation algorithms.
|
| AlgorithmIdentifiers |
Identifiers for the different contact recommendation algorithms available in
the library.
|
| AlgorithmParametersReader |
Class for reading contact recommendation / link prediction algorithms.
|
| AllNeighborsPropagationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an propagation mechanism that distributes pieces to all the neighbors of the propagating user.
|
| AllNeighborsPropagationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Given a single piece of information, a user selects all his/her neighbors as the destination of the piece.
|
| AllNotDiscardedNorPropagatedSightConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a sight mechanism that makes users observe all the information pieces which they have neither
discarded nor propagated.
|
| AllNotDiscardedNorPropagatedSightMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
This mechanism sees all the pieces of information who have not been previously discarded nor propagated.
|
| AllNotDiscardedSightConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a sight mechanism that makes users observe all the information pieces which they have not
discarded.
|
| AllNotDiscardedSightMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
This mechanism sees all the pieces of information who have not been previously discarded nor propagated.
|
| AllNotPropagatedExpirationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an expiration mechanism that discards all those received pieces which have not been propagated earlier.
|
| AllNotPropagatedExpirationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Expiration mechanism that discards every not previously propagated received information piece.
|
| AllNotPropagatedSightConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a sight mechanism that makes users observe all the information pieces which they have not
propagated.
|
| AllNotPropagatedSightMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Sight mechanism that selects every piece of information that has arrived and the user has not propagated earlier.
|
| AllNotRealPropagatedExpirationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an expiration mechanism that discards all the pieces which were not repropagated by the user
in the real diffusion procedure.
|
| AllNotRealPropagatedExpirationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Expiration mechanism that removes every information piece that has not been
repropagated in a real life scenario.
|
| AllNotRealPropagatedTimestampExpirationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an expiration mechanism that discards all the pieces which were not repropagated by the user
in the real diffusion procedure, and those which were repropagated in the real diffusion process are discarded
if their timestamp of repropagation has already passed.
|
| AllNotRealPropagatedTimestampExpirationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
If current timestamp is greater than the timestamp of the pieces, the elements
are discarded.
|
| AllRealPropagatedSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates a fixed number of own information pieces, and repropagate
all the received pieces which the user did repropagate in a real diffusion process.
|
| AllRealPropagatedSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Algorithm that chooses randomly some pieces from the own set of information pieces, and it only propagates
those received information pieces from other users that the user has propagated during the actual diffusion
procedure.
|
| AllRecommendedNeighborsPropagationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an propagation mechanism that distributes pieces to all the recommended neighbors of the propagating user.
|
| AllRecommendedNeighborsPropagationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Given a single piece of information, a user selects all the neighbors who can be reached
through a recommendation as the destination of the piece.
|
| AllRecommendedSightConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a sight mechanism that makes users observe all the information pieces coming from recommendation
links.
|
| AllRecommendedSightMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Sees the pieces of information that come from recommended users and the user has not previously propagated.
|
| AllSampler<U> |
Samples the all the possible links (all links not included in the test set).
|
| AllSamplerConfigurator<U> |
Class for configuring a sampling approach which takes all nodes.
|
| AllSightConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a sight mechanism that makes users observe everything they receive.
|
| AllSightMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Sight mechanism that selects every piece of information that has arrived to the user.
|
| AllTrainSightConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a sight mechanism that makes users observe all the information pieces coming from the original network
links.
|
| AllTrainSightMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Sees the pieces of information that come from training users and the user has not previously propagated.
|
| ALSUpdateableFactorizer<U,I> |
Updateable alternate least squares factorizer.
|
| AlternativeGiniFastGreedy<U> |
Alternative version of Fast Greedy algorithm for optimizing modularity, taking into account the Gini of the size
of communities.
|
| AlternativeSemiCompleteCommunityEdgeGiniComplement<U> |
Swap reranker that optimizes the Gini index of the distribution of edges between communities.
|
| AlternativeSemiCompleteCommunityEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| AlternativeSemiCompleteCommunityOuterEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| ASL<U> |
Computes the Average Shortest path Length of graphs.
|
| ASLGridSearch<U> |
Grid for the average shortest path length of a graph.
|
| ASLMode |
Algorithms for computing the average shortest path length of a graph (in case the graph is not strongly connected).
|
| Assortativity<U> |
Class for computing the assortativity of scalar values for a graph.
|
| AUC<U> |
Implementation of the area under the receiver-operating characteristic curve
for link prediction.
|
| AUCConfigurator<U,F> |
Grid search generator for area under the ROC curve.
|
| AutoRelation<W> |
Interface for defining the relation of a set of objects with themselves.
|
| AuxiliarMethods |
Class containing auxiliar methods for the Main functions.
|
| AuxiliarVariables |
Auxiliar variables for the execution examples.
|
| AverageCosineSimilarity<U> |
Recommender.
|
| AverageEmbeddednessRerankerGridSearch<U> |
Grid search for a reranker that optimizes the average embeddedness of the graph.
|
| AverageReciprocalShortestPathLength<U> |
Computes the Average Reciprocal Shortest path Length of graphs.
|
| AverageReciprocalShortestPathLengthGridSearch<U> |
Grid search for finding the average reciprocal shortest path length (ARSL) of the graph
|
| AverageWeaknessRerankerGridSearch<U> |
Grid search for a reranker that optimizes the average weakness of the graph.
|
| BackupSimulation |
Representation of the backup of a simulation.
|
| BalancedFastGreedy<U> |
Community detection algorithm for obtaining balanced communities, based on the FastGreedy algorithm
by M.E.J.
|
| BalancedFastGreedyConfigurator<U extends java.io.Serializable> |
Configurator for the balanced version of the FastGreedy community detection algorithm.
|
| Balancer<U> |
Definition of an algorithm that modifies a set of instances, so the classes are balanced.
|
| BarabasiGenerator<U> |
Generator for graphs following the Barabasi-Albert Preferential Attachment model for
graphs.
|
| BasicFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Basic implementation of a filter.
|
| BasicFilterConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for configuring a basic filter, which does not modify the data.
|
| BasicTypeIdentifiers |
Basic type identifiers for reading parameters from configuration files.
|
| BatchRecommenderSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates a fixed number of own information pieces, and repropagates
pieces which have been received through recommended links with a certain probability, and through not recommended
links with other.
|
| BatchRecommenderSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selects a set of information pieces to propagate depending on the recommendations.
|
| BidirectionalRumorSpreadingModelConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a bidirectional rumor spreading diffusion protocol.
|
| BidirectionalRumorSpreadingModelProtocol<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Adaptation of the pull-push protocol.
|
| BinaryDataReader |
Reads data from a binary file.
|
| BinaryDataWriter |
Writes data in a binary file.
|
| BinaryGraphReader |
Class for reading graph from binary files
|
| BinaryGraphWriter |
Writes a graph into a binary file.
|
| BinarySimulationReader<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Reads a simulation from a file.
|
| BinarySimulationWriter<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Writes a simulation into a file.
|
| BipartiteRecommender<U> |
Abstract class which represents a bipartite recommender.
|
| BIR<U> |
Binary independent retrieval algorithm, using a term-based query processing mechanism.
|
| BIRGridSearch<U> |
Grid search generator for Binary Independent Retrieval (BIR) algorithm.
|
| BIRSimilarity |
Similarity based on the BIR method from Information Retrieval.
|
| BM25<U> |
Adaptation of the BM-25 Information Retrieval Algorithm for user recommendation.
|
| BM25GridSearch<U> |
Grid search generator for the BM25 algorithm.
|
| BM25Similarity |
Similarity based on the BM25 method from Information Retrieval.
|
| CacheableItemDistanceModel<I> |
Item distance model which stores the distances in a cache.
|
| CentroidCBGridSearch<U> |
Grid search generator for centroid CB algorithm.
|
| CentroidCBRecommender<U> |
Content-based recommendation algorithm, based on a tf-idf scheme.
|
| CentroidCosineSimilarity<U> |
Recommender.
|
| Classifier<U> |
Methods for defining a supervised machine learning classifier.
|
| Closeness<U> |
Metric that computes the closeness of the nodes.
|
| ClosenessGridSearch<U> |
Grid for the closeness of a node.
|
| ClosenessMode |
Algorithms for computing the closeness of a node in a graph.
|
| Closure<U> |
Closure recommender.
|
| ClosureGridSearch<U> |
Grid search generator for Closure algorithm.
|
| ClusteringCoefficient<U> |
Computes the global clustering coefficient of a graph.
|
| ClusteringCoefficientComplement<U> |
Global reranker strategy that optimizes the clustering coefficient complement of
the network.
|
| ClusteringCoefficientComplement<U> |
Reranker strategy that optimizes the clustering coefficient complement of
the network.
|
| ClusteringCoefficientComplement<U> |
Reranker that tries to promote the opposite of the clustering coefficient of
the graph.
|
| ClusteringCoefficientComplement<U> |
Computes the complementary of the global clustering coefficient of a graph.
|
| ClusteringCoefficientComplementGridSearch<U> |
Grid for the complement of the clustering coefficient of a graph.
|
| ClusteringCoefficientComplementReranker<U> |
Swap reranker that demotes the global clustering coefficient of the network.
|
| ClusteringCoefficientComplementRerankerGridSearch<U> |
Grid search for a reranker that reduces the clustering coefficient of the network.
|
| ClusteringCoefficientGridSearch<U> |
Grid for the clustering coefficient of a graph.
|
| ClusteringCoefficientIncrement<U> |
Computes the increment of clustering coefficient if a link is added.
|
| ClusteringCoefficientIncrementGridSearch<U> |
Grid search for the metric which measures the increment in the global clustering coefficient of a network
if the pair was added.
|
| ClusteringCoefficientReranker<U> |
Swap reranker that promotes the global clustering coefficient of the network.
|
| ClusteringCoefficientRerankerGridSearch<U> |
Grid search for a reranker that promotes the clustering coefficient in the network.
|
| CombinedFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Combination of several filters, which are applied in a given order.
|
| CommDegreeGridSearch<U> |
Grid for the degree of a node.
|
| CommSizeGridSearch<U> |
Grid for the size of a community.
|
| Communities<U> |
Class that relates the nodes of a graph with communities.
|
| CommunitiesReader<U> |
Interface for reading communities from a file.
|
| CommunitiesWriter<U> |
Interface for writing communities to a file.
|
| CommunityDegree<U> |
Computes the community degree.
|
| CommunityDegreeGini<U> |
Computes the community degree Gini of the graph, i.e.
|
| CommunityDestinySize<U> |
Computes the average size of the destiny communities of the links.
|
| CommunityDestinySizeGridSearch<U> |
Grid Search for the destiny community size.
|
| CommunityDetectionAlgorithm<U> |
Algorithm for detecting the communities of a graph.
|
| CommunityDetectionConfigurationsReader |
Class for reading a community detection algorithm.
|
| CommunityDetectionConfigurator<U extends java.io.Serializable> |
Interface for configuring community detection algorithms.
|
| CommunityDetectionGridReader |
Class for reading a community detection algorithm.
|
| CommunityDetectionIdentifiers |
Identifiers for the different community detection algorithms available in the framework.
|
| CommunityDetectionParametersReader |
Class for reading a community detection algorithm.
|
| CommunityDetectionSelector<U extends java.io.Serializable> |
Given a parameter configuration, this class obtains the corresponding community detection
algorithms, so they can be applied over networks.
|
| CommunityDetector |
Program for computing community partitions of an individual network.
|
| CommunityEdgeGini<U> |
Computes the community edge Gini of the graph, i.e.
|
| CommunityFeatureData<U> |
Class for loading feature data from an index.
|
| CommunityGraphGenerator<U> |
Generates a multi-graph based on the community partition of a network.
|
| CommunityMetric<U> |
Global metric that depends on the communities of the graph.
|
| CommunityMetrics |
Automated unit tests for community metrics.
|
| CommunityRecallConfigurator<U,F> |
Grid search for configuring the community recall of the recommendations.
|
| CommunityReranker<U> |
Swap reranker for modifying it according to the community metrics of the network.
|
| CommunitySizeGini<U> |
Computes the Gini coefficient of the distribution of community sizes.
|
| CommunitySizeGiniGridSearch<U> |
Grid for the community size Gini complement of the graph.
|
| CommuteTime<U> |
Commute time algorithm.
|
| CommuteTimeGridSearch<U> |
Grid search generator for PageRank algorithm.
|
| CommuteTimePersPageRankGridSearch<U> |
Grid search generator for PageRank algorithm.
|
| ComplementaryCommunityMetric<U> |
Computes a global community metric over the complementary graph.
|
| ComplementaryDegree<U> |
Computes the degree of a given user in a graph.
|
| ComplementaryDegreeGridSearch<U> |
Grid for computing the degree of a node in the complementary graph.
|
| ComplementaryEmbededness<V> |
Computes the embeddedness the edges in the complementary of a graph.
|
| ComplementaryEmbedednessGridSearch<U> |
Grid for the embeddedness of a pair in the complementary graph.
|
| ComplementaryFOAFGridSearch<U> |
Grid for the neighbor overlap of a pair of users in the complementary graph.
|
| ComplementaryGraph<U> |
Wrapper for the complementary graph of another one given.
|
| ComplementaryGraphGenerator<U> |
Generates complementary graphs.
|
| ComplementaryGraphMetric<U> |
Computes a graph metric over the complementary graph.
|
| ComplementaryIndividualCommunityMetric<U> |
Computes an individual community metric over the complementary graph.
|
| ComplementaryInverseDegree<U> |
Computes the degree of a given user in a graph.
|
| ComplementaryInverseDegreeGridSearch<U> |
Grid for the inverse degree of a node in the complementary graph.
|
| ComplementaryLocalClusteringCoefficient<U> |
Computes the local clustering coefficient of a node in the complementary graph.
|
| ComplementaryLocalClusteringCoefficientGridSearch<U> |
Grid for the local clustering coefficient of a node in the complementary graph.
|
| ComplementaryNeighbourOverlap<U> |
Computes the intersection between the neighborhoods of two nodes in the complementary graph.
|
| ComplementaryPageRank<U> |
Computes the PageRank values in the complementary graph for the different nodes in the graph.
|
| ComplementaryPageRankGridSearch<U> |
Grid for the PageRank value of a node in the complementary graph.
|
| ComplementaryPairMetric<U> |
Computes a pair metric over the complementary graph.
|
| ComplementaryVertexMetric<U> |
Computes a vertex metric over the complementary graph.
|
| CompleteCommunityDegreeGini<U> |
Computes the community degree Gini of the graph, i.e.
|
| CompleteCommunityDegreeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| CompleteCommunityDegreeGiniGridSearch<U> |
Grid for the complete community degree Gini of the graph.
|
| CompleteCommunityDegreeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the degrees of the communities (restricted
to links between communities).
|
| CompleteCommunityEdgeGini<U> |
Computes the community edge Gini of the graph, i.e.
|
| CompleteCommunityEdgeGiniComplement<U> |
Swap reranker that optimizes the Gini index of the distribution of edges between communities.
|
| CompleteCommunityEdgeGiniGridSearch<U> |
Grid for the complete community edge gini of the graph.
|
| CompleteCommunityEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| CompleteCommunityGraphGenerator<U> |
Generates a multi-graph which contains all communities as nodes and all links between
communities (different or not) as edges.
|
| CompleteCommunityNoSelfLoopsGraphGenerator<U> |
Generates a multi-graph which contains all communities as nodes and all links between
communities (different or not) as edges.
|
| CompleteCommunityOuterDegreeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the degrees of the communities (restricted
to links between communities).
|
| CompleteCommunityOuterEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| CompleteCommunityReranker<U> |
Reranker that uses community metrics of the user graph.
|
| CompleteCommunityReranker<U> |
Global reranker for computing metrics that only use links between pairs of communities.
|
| CompleteDistanceCalculator<U> |
Computes some of the distance based metrics: distances, number of geodesic paths between two nodes, betweenness.
|
| CompleteEdgeGini<U> |
Computes the value for Gini for all links between pairs of nodes.
|
| CompleteEdgeGiniGridSearch<U> |
Grid for the edge Gini between all pairs of nodes in a graph.
|
| CompleteGraphGenerator<U> |
Class for generating complete graphs.
|
| CompTuple2oo<X extends java.lang.Comparable<X>,Y extends java.lang.Comparable<Y>> |
Comparable version of Tuple2oo.
|
| Config |
List of routes for specific index elements.
|
| Configurations |
Class for storing the different possible configurations for an algorithm, metric, etc.
|
| ConfigurationsReader |
Class for reading parameters from a YAML file.
|
| ContactRecommendationRelevanceModel<U> |
Relevance model for the specific contact recommendation task.
|
| ContainsInformationFeatureFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Filter that keeps only those information pieces which contain an information feature
corresponding to a certain field (i.e.
|
| ContainsInformationFeatureFilterConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for configuring a basic filter, which leaves only those information pieces containing
any from a family of filters.
|
| Content<T,C> |
User-created content.
|
| Coreness<U> |
Computes the coreness (or core number) of the nodes.
|
| CorenessGridSearch<U> |
Grid for the coreness of a node.
|
| CorenessTest |
Automated unit tests for the coreness metric.
|
| Cosine<U> |
Recommender using the cosine similarity to produce recommendations.
|
| CosineGridSearch<U> |
Grid search generator for Cosine similarity algorithm.
|
| CosineSimilarity |
Similarity based on the Salton index (a.k.a.as cosine similarity).
|
| CountRealPropagatedSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates a fixed number of own information pieces, and repropagate
some of the received pieces which the user did repropagate in a real diffusion process.
|
| CountRealPropagatedSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selection mechanism that chooses randomly a fixed number of information pieces owned by the propagating user, and,
from the received ones, it randomly chooses a fixed number of pieces which the user did propagate during the actual
diffusion procedure (in a real life scenario).
|
| CountSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates a fixed number of own information pieces, and a
fixed number of the received pieces.
|
| CountSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selects the propagated pieces.
|
| CountSightConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a sight mechanism that makes users observe a limited amount of information pieces.
|
| CountSightMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
The user sees (at most) a fixed number of (different) information pieces each iteration.
|
| CountThresholdModelConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a protocol in which propagates the received information if enough neighbors send the same piece to him/her.
|
| CountThresholdModelProtocol<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Count threshold model protocol.
|
| CountThresholdSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates a fixed number of own information pieces, and repropagates
pieces which have been received more than a fixed number of times.
|
| CountThresholdSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selection mechanism that only propagates those received pieces which have been received (at least) a fixed
number of times.
|
| CreatorGlobalEntropy<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Computes the entropy over the set of users in the network.
|
| CreatorGlobalEntropyConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the entropy over the set of creators whose information has been received by each user
in the network.
|
| CreatorGlobalGiniComplement<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Computes the Gini complement over the set of users in the network.
|
| CreatorGlobalGiniComplementConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the complement of the Gini coefficient over the set of creators whose information has been received by each user
in the network.
|
| CreatorIndividualEntropy<U extends java.io.Serializable,I extends java.io.Serializable,F> |
For each user in the network, this metric computes the entropy over
the users in the network who have created an information piece that has been received by the user.
|
| CreatorIndividualEntropyConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the entropy over the set of creators whose information has been received by each user
in the network.
|
| CreatorIndividualGiniComplement<U extends java.io.Serializable,I extends java.io.Serializable,F> |
For each user in the network, this metric computes the complement of the Gini distribution over
the users in the network who have created an information piece that has been received by the user.
|
| CreatorIndividualGiniComplementConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that, for each user in the network, obtains the number of times that has
that measures the complement of the Gini coefficient over the set of creators whose information has been received by each user
in the network.
|
| CreatorRecall<U extends java.io.Serializable,I extends java.io.Serializable,F> |
For each user in the network, this metric computes the proportion of users in the network who have created
an information piece that has been received by the user (i.e.
|
| CreatorRecallConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the fraction of people discovered by each user in the network.
|
| CustomProtocol<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for building custom protocols.
|
| CustomProtocolConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a custom protocol.
|
| Data<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class that contains the basic information for simulations.
|
| DataFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for filtering unnecessary data for simulations.
|
| DataReader<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for reading the data.
|
| Degree<U> |
Computes the degree of a given user in a graph.
|
| DegreeAssortativity<U> |
Class for computing the degree assortativity in a graph.
|
| DegreeAssortativityGridSearch<U> |
Grid search for the degree assortativity metric
|
| DegreeGini<U> |
Computes the Gini metric between the different nodes in the graph (auto-nodes are
not taken into account).
|
| DegreeGiniComplementRerankerGridSearch<U> |
Grid search for a reranking approach that minimizes the Gini index of the degree
distribution of the network.
|
| DegreeGiniGridSearch<U> |
Grid for the degree gini of the graph.
|
| DegreeGiniReranker<U> |
Optimizes the degree Gini of a graph.
|
| DegreeGridSearch<U> |
Grid for the degree of a node.
|
| DegreePearsonCorrelation<U> |
Computes the degree Pearson correlation for the links in a graph.
|
| DegreePearsonCorrelationGridSearch<U> |
Grid search for the degree Pearson correlation metric
|
| Dendogram<U> |
Abstract class that represents a dendogram and its functions.
|
| DendogramCommunityDetectionAlgorithm<U> |
Algorithm for detecting the dendogram of communities in a graph.
|
| DendogramTest |
Automated unit tests for the dendogram class.
|
| Density<U> |
Computes the density of a graph.
|
| DensityGridSearch<U> |
Grid for the density of the graph.
|
| DFRee<U> |
Class that applies the DFRee Divergence from Randomness model as a contact
recommendation algorithm.
|
| DFReeGridSearch<U> |
Grid search generator for the DFRee Divergence From Randomness method.
|
| DFReeKLIM<U> |
Class that applies the DFReeKLIM Divergence from Randomness model as a contact
recommendation algorithm.
|
| DFReeKLIMGridSearch<U> |
Grid search generator for the DFReeKLIM Divergence From Randomness method.
|
| DFReeKLIMSimilarity |
Similarity based on the DFReeKLIM method on Information Retrieval.
|
| DFReeSimilarity |
Similarity based on the DFRee model for Information Retrieval
|
| Diameter<U> |
Computes the diameter of a network.
|
| DiameterGridSearch<U> |
Grid for the diameter of the graph.
|
| DiceCommunityEdgeGini<U> |
Computes the Dice community edge Gini of the graph, i.e.
|
| DiceCompleteCommunityEdgeGini<U> |
Computes the Dice community edge Gini of the graph, i.e.
|
| DiceCompleteCommunityEdgeGiniGridSearch<U> |
Grid for the Dice Complete Community Edge Gini metric.
|
| DiceInterCommunityEdgeGini<U> |
Computes the Dice community edge Gini of the graph, i.e.
|
| DiceInterCommunityEdgeGiniGridSearch<U> |
Grid for the Dice Inter-Community Edge Gini metric.
|
| DiceSemiCompleteCommunityEdgeGini<U> |
Computes the Dice community edge Gini of the graph, i.e.
|
| DiceSemiCompleteCommunityEdgeGiniGridSearch<U> |
Grid for the Dice Complete Community Edge Gini metric.
|
| Diffusion |
Executes an information diffusion procedure over a network.
|
| DiffusionEvaluation |
Given the outcome of a simulation procedure, measures its different properties and distributions.
|
| DirectedEdges |
Interface for the directed edges.
|
| DirectEdgeMetricReranker<U> |
Global reranker strategy that optimizes the average value of an edge metric.
|
| DirectedGraph<V> |
Interface for directed graphs.
|
| DirectedJungGraph<U> |
Directed Graph Wrapper for JUNG
|
| DirectedMultiEdges |
Class for the directed multi-edges.
|
| DirectedMultiGraph<U> |
Interface for directed multi graphs.
|
| DirectedUnweightedComplementaryGraph<U> |
Directed unweighted complementary graph.
|
| DirectedUnweightedGraph<V> |
Interface for directed unweighted graphs.
|
| DirectedUnweightedGraphTest |
Class that tests the fast directed unweighted implementation of graphs.
|
| DirectedUnweightedGraphTest |
Class that tests the fast directed unweighted implementation of graphs.
|
| DirectedUnweightedMultiGraph<V> |
Interface for directed unweighted multigraphs
|
| DirectedUnweightedMultigraphTest |
Class for testing the fast implementation of directed unweighted multigraphs.
|
| DirectedWeightedComplementaryGraph<U> |
Directed weighted complementary graph.
|
| DirectedWeightedGraph<V> |
Interface for directed weighted graphs.
|
| DirectedWeightedGraphTest |
Class for testing the fast implementation for directed weighted graphs
|
| DirectedWeightedGraphTest |
Class for testing the fast implementation for directed weighted graphs
|
| DirectedWeightedMultiGraph<U> |
Interface for directed weighted multigraphs
|
| DirectedWeightedMultigraphTest |
Class for testing the fast implementation of a directed weighted multigraph
|
| DirectGraphMetricReranker<U> |
Global reranker strategy that reorders the candidate users for promoting a graph metric.
|
| DirectGraphMetricReranker<U> |
Reranker strategy that reorders the candidate users for promoting a graph metric.
|
| DirectGraphMetricReranker<U> |
Individual reranker, which reorders a recommendation to promote
a graph metric.
|
| Dist2Popularity<U> |
Recommender that sorts users at distance 2 by popularity.
|
| Distance<U> |
Computes the distance between nodes.
|
| Distance2Degree<U> |
Metric that finds the number of different neighbors at distance 2 from a user.
|
| DistanceCalculator<U> |
Interface that defines methods for computing distance-based metrics for a network and retrieving them.
|
| DistanceGridSearch<U> |
Grid search for the distance.
|
| DistanceMetricsTest |
Automatic unit tests for distance-based metrics.
|
| DistanceTwoIndividualSampler<U> |
Samples the complete set of users at distance two from the user
|
| DistanceTwoIndividualSamplerConfigurator<U> |
Class for configuring a sampling approach which takes all nodes at distance two from the target user.
|
| DistanceTwoLinkPredictionIndividualSampler<U> |
Samples all the links created at distance two from the user in a test graph,
and the same amount of links at distance two which have not been created.
|
| DistanceTwoLinkPredictionIndividualSamplerConfigurator<U> |
Class for selecting nodes at distance 2 from the target user, considering the usual approach in link prediction,
i.e.
|
| DistanceWithoutLink<U> |
Computes the distance between two nodes in the network, considering that the link does not exist.
|
| DistanceWithoutLinkGridSearch<U> |
Grid search for the distance between two users if we removed the link between them.
|
| Distribution<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for defining a distribution of elements.
|
| DistributionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for configuring a distribution on an information diffusion process.
|
| DistributionIdentifiers |
The list of identifiers of the distributions.
|
| DistributionParameterReader |
Reads the parameter for a distribution during information diffusion simulations.
|
| DistributionSelector<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for selecting a distribution.
|
| DLH<U> |
Class that applies the DLH Divergence from Randomness model as a contact
recommendation algorithm.
|
| DLHGridSearch<U> |
Grid search generator for the DLH Divergence From Randomness method.
|
| DLHSimilarity |
Similarity based on the DLH model for Information Retrieval.
|
| DocumentMap<C> |
Document map containing information about the documents in an index.
|
| DPH<U> |
Class that applies the DPH Divergence from Randomness model as a contact
recommendation algorithm.
|
| DPHGridSearch<U> |
Grid search generator for the DPH Divergence From Randomness method.
|
| DPHSimilarity |
Similarity based on the DPH model for Information Retrieval.
|
| EBM25<U> |
Adaptation of an extreme version of the BM25 algorithm, where the k parameter tends to infinity, without term discrimination.
|
| EBM25GridSearch<U> |
Grid search generator for the Extreme BM25 algorithm.
|
| Eccentricity<U> |
Metric that computes the eccentricity of the nodes.
|
| EccentricityGridSearch<U> |
Grid for the eccentricity of a node.
|
| EdgeBetweenness<U> |
Computes the edge betweenness of the graph.
|
| EdgeBetweennessGridSearch<U> |
Grid search for the betweenness.
|
| EdgeGini<U> |
Computes the value for Gini for the different pairs of nodes.
|
| EdgeGiniMode |
Different execution modes for the PairGini metric.
|
| EdgeMetricReranker<U> |
Global reranker strategy that reorders the candidate users according to
an edge metric that we want to optimize.
|
| EdgeMetricReranker<U> |
Reranker strategy that optimizes the average value of an edge metric.
|
| EdgeMetricReranker<U> |
Abstract implementation of a reranking algorithm that modifies the ranking according
to the values of an edge metric.
|
| EdgeOrientation |
Indicates the orientation of the edges to take.
|
| Edges |
Interface that represents the edges of a graph.
|
| EdgeType |
Class that represents the type of the edges.
|
| EdgeWeight |
Class that represents the weight of the edges.
|
| EdgeWeight<V> |
Finds the weight of an edge in a graph.
|
| EdgeWeightGridSearch<U> |
Grid search for the edge weight.
|
| EigenvectorCentrality<U> |
Finds the eigenvector centrality of the network, which measures the importance of a node
based on the importance of its neighbors.
|
| EigenvectorCentralityGridSearch<U> |
Grid for the eigenvector centrality of a node.
|
| Embededness<U> |
Computes the embeddedness the pairs of nodes of a graph.
|
| EmbedednessGridSearch<U> |
Grid for the embeddedness of a pair of users.
|
| EmbedednessReranker<U> |
Swap reranker for optimizing the average embeddedness of the graph.
|
| EmptyFeatureFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
For each information piece without no features, it adds a new feature, with value 1.0
|
| EmptyFeatureFilterConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for configuring a filter that adds, for each information piece without any feature, an empty feature.
|
| EmptyGraphGenerator<U> |
Empty graph generator.
|
| EmptyMultiGraphGenerator<U> |
Creates an empty multigraph
|
| EmptyTreeGenerator<U> |
Empty tree generator.
|
| EmptyWriter<U,I> |
Class for storing / reading recommendations on RAM memory.
|
| Entropy |
Computes the entropy of a series.
|
| ErdosGenerator<U> |
Generates a random graph following the Erdös-Renyi model.
|
| ERRIAConfigurator<U,F> |
Grid search for configuring the ERRIA of the recommendations.
|
| Evaluation |
Program for applying a given reranking algorithm to the outcome of a contact recommendation algorithm.
|
| ExpandedFOAFCountGridSearch<U> |
Grid for the expanded number of common neighbors of a pair of users, weighted by the number of times
a neighbor appears.
|
| ExpandedFOAFGridSearch<U> |
Grid for the expanded number of common neighbors of a pair of users.
|
| ExpandedNeighborCountedOverlap<U> |
Expanded neighbor overlap.
|
| ExpandedNeighborOverlap<U> |
Expanded neighbor overlap.
|
| ExpirationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for configuring an expiration mechanism.
|
| ExpirationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Interface for checking the expiration of the information pieces.
|
| ExpirationMechanismIdentifiers |
Identifiers for the different expiration mechanisms for information propagation protocols available in
the framework.
|
| ExpirationParameterReader |
Class for reading an expiration mechanism for information diffusion.
|
| ExpirationSelector<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for selecting an expiration mechanism from its configuration.
|
| ExponentialDecayExpirationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an expiration mechanism that increases the probability of discarding a piece over time.
|
| ExponentialDecayExpirationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Expiration mechanism that increases exponentially the probability of discarding
an information piece as the number of iterations since its creation increases.
|
| ExternalFeatureGlobalGiniComplement<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Metric that computes the complement of the Gini coefficient over the different features unknown to the different
users.
|
| ExternalFeatureGlobalGiniConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the complement of the Gini coefficient over those features unknown by the users.
|
| ExternalFeatureGlobalRate<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Metric that computes the rate of features received by the different users which were unknown by the receiver
(we understand as external features those information features which are not present in the information pieces
created by the users, or those user features different from the receiver's ones).
|
| ExternalFeatureGlobalRateConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the proportion of the received features unknown to the
users (globally)
|
| ExternalFeatureIndividualGiniComplement<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Computes the complement of the Gini coefficient over the distribution of the features that the user
does not already know.
|
| ExternalFeatureIndividualGiniComplementConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the complement of the Gini coefficient over those features unknown by the user.
|
| ExternalFeatureIndividualRate<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Computes the proportion of features that reach a user and are unknown to him/her.
|
| ExternalFeatureIndividualRateConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the proportion of the received features unknown to the
users.
|
| ExternalFeatureRecall<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Estimates the fraction of the unknown features of a user have been discovered thanks to the diffusion.
|
| ExternalFeatureRecallConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the fraction of the unknown features that a user has discovered.
|
| ExtremeBM25Similarity |
Similarity based on the Extreme BM25 method from Information Retrieval.
|
| F1Score<U> |
Implementation of the F1 score metric for link prediction.
|
| F1ScoreConfigurator<U,F> |
Grid search generator for the F1 score of the link prediction method.
|
| FastDirectedUnweightedEdges |
Fast implementation of directed unweighted edges.
|
| FastDirectedUnweightedGraph<V> |
Fast implementation for a directed unweighted graph.
|
| FastDirectedUnweightedMultiEdges |
Fast implementation of directed unweighted edges for multigraphs.
|
| FastDirectedUnweightedMultiGraph<U> |
Fast implementation for a directed unweighted multi-graph.
|
| FastDirectedWeightedEdges |
Fast implementation of directed weighted edges.
|
| FastDirectedWeightedGraph<V> |
Fast implementation of a directed weighted graph.
|
| FastDirectedWeightedMultiEdges |
Fast implementation of directed weighted edges for multigraphs.
|
| FastDirectedWeightedMultiGraph<U> |
Fast implementation of a directed weighted graph.
|
| FastDistanceCalculator<U> |
Fast version of a distance calculator which just computes the distances between pairs of nodes.
|
| FastEdges |
Abstract fast implementation of class Edges.
|
| FastFiller<U,I> |
Fast version of the filler interface.
|
| FastGiniIndex |
Class for computing and updating the Gini index.
|
| FastGraph<U> |
Interface for fast implementations of graphs.
|
| FastGraphIndex<U> |
Class that represents both user and item indexes for a graph.
|
| FastGreedy<U> |
Fast Greedy algorithm for optimizing modularity.
|
| FastGreedyConfigurator<U extends java.io.Serializable> |
Configures the FastGreedy community detection algorithm.
|
| FastImplicitMFGridSearch<U> |
Grid search generator for the fast Implicit Matrix Factorization algorithm by
Pilászy, Zibriczky and Tikk (PZT) algorithm.
|
| FastIndex<T> |
Fast implementation of a generic index.
|
| FastIndexReader<U> |
Reads an index from a file.
|
| FastMultiEdges |
Abstract fast implementation of class MultiEdges.
|
| FastMultiGraph<U> |
Interface for fast implementations of multi-graphs.
|
| FastTree<U> |
Fast implementation of the tree.
|
| FastUndirectedUnweightedEdges |
Fast implementation of undirected unweighted edges.
|
| FastUndirectedUnweightedGraph<V> |
Fast implementation of an undirected unweighted graph.
|
| FastUndirectedUnweightedMultiEdges |
Fast implementation of undirected unweighted edges for multigraphs.
|
| FastUndirectedUnweightedMultiGraph<U> |
Fast implementation of an undirected unweighted multi-graph
|
| FastUndirectedWeightedEdges |
Fast implementation of undirected weighted edges.
|
| FastUndirectedWeightedGraph<V> |
Fast implementation for an Undirected Weighted graph.
|
| FastUndirectedWeightedMultiEdges |
Fast implementation of undirected weighted edges for multigraphs.
|
| FastUndirectedWeightedMultiGraph<U> |
Fast implementation for an Undirected Weighted multigraph.
|
| FastUnweightedAutoRelation<W> |
Fast implementation for an unweighted relation of objects with themselves.
|
| FastUnweightedPairwiseRelation<W> |
Unweighted relation between different types of objects.
|
| FastUnweightedRelation<W> |
Fast implementation of an unweighted relation.
|
| FastUnweightedTree<U> |
Fast implementation of an unweighted tree
|
| FastUpdateableFeatureIndex<F> |
Fast and updateable version of a FeatureIndex, where features are internally represented with numerical indices from 0 (inclusive) to the number of indexed features (exclusive).
|
| FastUpdateableGraphIndex<U> |
Class that represents both user and item indexes for a graph.
|
| FastUpdateableItemIndex<I> |
Fast updateable version of ItemIndex, where items are internally represented with numerical indices from 0 (inclusive) to the number of indexed items (exclusive).
|
| FastUpdateablePointWisePreferenceData<U,I> |
Fast updateable version of a pointwise preference data.
|
| FastUpdateablePreferenceData<U,I> |
Interface for updateable preference data.
|
| FastUpdateableRankingRecommender<U,I> |
Fast updateable recommender that ranks the user.
|
| FastUpdateableRecommender<U,I> |
Interface for defining recommendation algorithms which can be updated over time.
|
| FastUpdateableUserIndex<U> |
Fast and updateable version of UserIndex, where users are internally represented with numerical indices from 0 (inclusive) to the number of indexed users (exclusive).
|
| FastUser<U> |
Fast implementation for users.
|
| FastWeightedAutoRelation<W> |
Fast implementation for a weighted auto relation.
|
| FastWeightedPairwiseRelation<W> |
Fast implementation for a weighted relation.
|
| FastWeightedRelation<W> |
Fast implementation of a weighted relation.
|
| FastWeightedTree<U> |
Fast implementation of a weighted tree.
|
| Feature<F> |
Class for the parameters we want to measure at evaluation.
|
| Feature |
Stores the information about an attribute.
|
| FeatureGlobalEntropy<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Metric that computes the entropy over the number of times each feature has been received.
|
| FeatureGlobalEntropyConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the proportion of the received features unknown to the
users.
|
| FeatureGlobalGiniComplement<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Metric that computes the complement of the Gini coefficient over the different features.
|
| FeatureGlobalGiniComplementConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the Gini complement over the features which have been received by the users.
|
| FeatureGlobalKLDivergence<U extends java.io.Serializable,I extends java.io.Serializable,F> |
This global metric computes the number of bytes of information we expect to lose
if we approximate the real distribution of features with the estimated distribution
obtained from simulating.
|
| FeatureGlobalKLDivergenceConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the KL divergence over the features which have been received by the users.
|
| FeatureGlobalKLDivergenceInverse<U extends java.io.Serializable,I extends java.io.Serializable,P> |
This global metric computes the number of bytes of information we expect to lose
if we approximate the observed distribution of the parameters with their prior distribution
(i.e.
|
| FeatureGlobalUserEntropy<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Computes the entropy over the different features.
|
| FeatureGlobalUserEntropyConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the entropy over the different features, where, for each feature,
we measure the number of users who have received it.
|
| FeatureGlobalUserGiniComplement<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Computes the complement of the Gini coefficient over the different features.
|
| FeatureGlobalUserGiniComplementConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the complement of the Gini coefficient over the different features, where, for each feature,
we measure the number of users who have received it.
|
| FeatureIndividualEntropy<U extends java.io.Serializable,I extends java.io.Serializable,P> |
It computes the entropy of the distribution of times that the different values
of a user or information piece feature has reached the different users in the network
during a simulation.
|
| FeatureIndividualEntropyConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the entropy of the features that a single user has received.
|
| FeatureIndividualGini<U extends java.io.Serializable,I extends java.io.Serializable,F> |
It computes the Gini complement of the distribution of times that the different values
of a user or information piece feature has reached the different users in the network
during a simulation.
|
| FeatureIndividualGiniComplementConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the complement of the Gini coefficient of the features that a single user has received.
|
| FeatureIndividualKLDivergence<U extends java.io.Serializable,I extends java.io.Serializable,F> |
This individual metric computes the number of bytes of information we expect to lose
if we approximate the real distribution of features of the users (the total frequency of appearance
of the features over the information pieces) with the estimated distribution
obtained from simulating.
|
| FeatureIndividualKLDivergenceConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the Kullback-Leibler divergence of the features that a single user has received.
|
| FeatureInformation |
Class for storing some information about the features for ML patterns.
|
| FeatureKLDivergenceInverse<U extends java.io.Serializable,I extends java.io.Serializable,F> |
This individual metric computes the number of bytes of information we expect to lose
if we approximate the observed distribution of the parameters received by the user
with their prior distribution (i.e.
|
| FeatureRecall<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Computes the fraction of all the features that each user has received during the diffusion process.
|
| FeatureRecallConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the fraction of the features that a user has discovered.
|
| Features |
A class for storing the set of attributes which might be used by a machine
learning approach.
|
| FeatureType |
Types of the features.
|
| FeatureType |
Enumeration for the different types that a feature can take.
|
| Filler<U,I> |
Methods for classes that might be used to complete recommendation lists which
do not fill themselves due to coverage problems of the algorithm.
|
| FilterConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for configuring a data filter for information diffusion from
a given set of parameters.
|
| FilterIdentifiers |
Identifiers for the different data filters for information diffusion which are available in
the framework.
|
| FilterParameterReader |
Class for reading a filter for information diffusion.
|
| FilterSelector<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for selecting and configuring a filter for the information diffusion
process from a set of parameters.
|
| FOAFGridSearch<U> |
Grid for the neighbor overlap of a pair of users.
|
| ForwardIndex<C> |
Interface for defining a forward index.
|
| FreeDiscovery<U> |
Finds how unpopular the user is in the network.
|
| FreeDiscoveryGridSearch<U> | |
| FreqVector |
Frequency vector for forward indexes.
|
| Generator<V> |
Generates objects of a certain type.
|
| GeneratorBadConfiguredException |
Exception for bad configured generators.
|
| GeneratorNotConfiguredException |
Exception for unconfigured generators.
|
| Generators |
Generator examples.
|
| GenericIndex<T> |
Bi-map-like structure to back fast version of indexes.
|
| Geodesics<U> |
Measures the number of geodesic paths between two different nodes in the network.
|
| GeodesicsGridSearch<U> |
Grid search for the number of shortest paths between two nodes.
|
| GiniIndex |
Computes the value of the Gini Index of a list of values.
|
| GiniWeightedFastGreedy<U> |
Alternative version of Fast Greedy algorithm for optimizing modularity, taking into account the Gini of the size
of communities.
|
| GiniWeightedFastGreedyConfigurator<U extends java.io.Serializable> |
Configurator for the balanced version of the FastGreedy community detection algorithm that tries
to optimize modularity and Gini of the community sizes.
|
| GirvanNewman<U> |
Implementation of the Girvan-Newman community detection algorithm, based on removing edges with the highest
betweenness value.
|
| GirvanNewmanConfigurator<U extends java.io.Serializable> |
Configurator for the Girvan-Newman community detection algorithm, which divides the network in communities
by removing the edge with the highest betweenness.
|
| GlobalCommunityMetricGridSearch<U> |
Class for performing the grid search for a given global community metric.
|
| GlobalCommunityMetricIdentifiers |
Identifiers for edge metrics.
|
| GlobalCommunityMetricSelector<U> |
Class that translates from a grid to the different contact recommendation algorithns.
|
| GlobalLHNIndex<U> |
Global Leicht-Holme-Newman similarity algorithm.
|
| GlobalLHNIndexGridSearch<U> |
Grid search generator for global LHN index algorithm.
|
| GlobalMatrixBasedRecommender<U> |
Contact recommendation algorithm that on operations over a global matrix.
|
| GlobalRankingGreedyReranker<U,I> |
Implementation of a greedy reranking strategy for optimizing global properties of the system.
|
| GlobalRankingLambdaReranker<U,I> |
Implementation of a greedy reranking strategy for optimizing global properties of the system.
|
| GlobalReranker<U,I> |
Interface for defining reranking strategies which change the position of items in recommendation lists
to optimize global properties of the system beyond relevance.
|
| GlobalRerankerFunction<U> |
Functions for retrieving reranking algorithms.
|
| GlobalSimulationMetric<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for the different global metrics (applied over the whole set
of users) to apply over the simulation.
|
| Graph<V> |
Interface for a generic graph.
|
| GraphAnalyzer |
Program that given a network (and, if available, some community partitions), computes several properties of the network.
|
| GraphCloneGenerator<U> |
Class for cloning graphs.
|
| GraphGenerationAlgorithms |
A list containing the names of graph generation algorithms.
|
| GraphGenerator<U> |
Generates different graphs.
|
| GraphIndex<U> |
Class that represents both user and item indexes for a graph.
|
| GraphLocalReranker<U> |
Generalization of greedy local reranking strategies, for processing several recommendations at a time.
|
| GraphMetric<U> |
Interface for global graph metrics.
|
| GraphMetricFunction<U> |
Functional interface for retrieving global graph metrics.
|
| GraphMetricGridSearch<U> |
Class for performing the parameter configuration of global structural network metrics.
|
| GraphMetricIdentifiers |
Identifiers for edge metrics.
|
| GraphMetricReranker<U> |
Global reranker strategy that reorders the candidate users according to
a graph metric.
|
| GraphMetricReranker<U> |
Reranker strategy that reorders the candidate users according to
a graph metric.
|
| GraphMetricReranker<U> |
Individual reranker, which reorders a recommendation according to
a graph metric.
|
| GraphMetricSelector<U> |
Class that translates from a grid to the different global metrics of the social network graph.
|
| GraphMetricsEvaluation |
Class for analyzing the properties of a graph after adding the outcome of a contact recommendation / link prediction
algorithm.
|
| GraphMetricsTest |
Automated unit tests for metrics that affect the whole network.
|
| GraphReader<V> |
Interface for graph readers.
|
| GraphSimilarity |
Abstract class for representing similarities extracted from graph properties.
|
| GraphSimpleFastPreferenceData<U> |
Simple implementation of FastPreferenceData backed by nested lists.
|
| GraphSimplePreferenceData<U> |
Simple map-based preference data for social network evaluation.
|
| GraphSimpleUpdateableFastPreferenceData<U> |
Implementation of a fast updateable version of preference data for social network
analysis, based on social network graphs.
|
| GraphSwapReranker<U> |
Abstract implementation of the swap reranking strategy for the contact recommendation context.
|
| GraphWriter<V> |
Interface for graph writers.
|
| Grid |
A grid containing all the possible values for the different parameters of
an algorithm, metric, etc.
|
| GridReader |
Class for reading a grid of parameters from a YAML file.
|
| HarmonicCentrality<U> |
Metric that computes the harmonic centrality of the nodes (a version of closeness that
uses the harmonic mean of the distances from the target node to the rest of nodes in the
network.
|
| HarmonicCentralityGridSearch<U> |
Grid for the harmonic centrality of a node.
|
| HeuristicAverageEmbeddednessRerankerGridSearch<U> |
Grid search for a reranker that optimizes the average embeddedness of the graph using
heuristic approximations.
|
| HeuristicAverageWeaknessRerankerGridSearch<U> |
Grid search for a reranker that optimizes the average weakness of the graph using
heuristic approximations.
|
| HeuristicEmbedednessReranker<U> |
Swap reranker for optimizing the embeddedness of the graph.
|
| HeuristicWeaknessReranker<U> |
Swap reranker for optimizing the embeddedness of the graph.
|
| HITS<U> |
Hiperlink-Induced Topic Search (HITS) recommender.
|
| HITS<U> |
Computes the HITS values of the different nodes in a graph.
|
| HITSGridSearch<U> |
Grid search generator for the HITS algorithm.
|
| HITSGridSearch<U> |
Grid for the HITS value of a node.
|
| HittingTimeGridSearch<U> |
Grid search generator for PageRank algorithm.
|
| HittingTimePersPageRankGridSearch<U> |
Grid search generator for PageRank algorithm.
|
| HKVUpdateableFactorizer<U,I> |
Implicit matrix factorization of Hu, Koren and Volinsky.
|
| HubDepressedIndex<U> |
Recommender that uses the hub depressed index of the neighbors: given the number of common neighbors
between two users, the recommendation score is divided by the size of either the target user or the candidate user:
the user with a larger number of them.
|
| HubDepressedIndexGridSearch<U> |
Grid search generator for Hub Depressed Index (HDI) algorithm.
|
| HubPromotedIndex<U> |
Recommender that uses the hub depressed index of the neighbors: given the number of common neighbors
between two users, the recommendation score is divided by the size of either the target user or the candidate user:
the user with a smaller number of them.
|
| HubPromotedIndexGridSearch<U> |
Grid search generator for Hub Promoted Index (HPI) algorithm.
|
| IdFiller<U,I> |
Filler that completes rankings by sorting the remaining items by id.
|
| IdxValue<W> |
Class for expressing weights.
|
| ILD<U,I> |
Global version of EILD.
|
| ImplFreqVector |
Implementation of a frequency vector
|
| ImplicitMFGridSearch<U> |
Grid search generator for the Implicit Matrix Factorization algorithm by
Hu, Koren and Volinsky (HKV) algorithm.
|
| ImplTermFreq |
Implementation of the TermFreq class
|
| IndependentCascadeModelConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures the independent cascade model protocol, where the repropagation of information depends only
on the users who receive and propagate such information.
|
| IndependentCascadeModelProtocol<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Independent Cascade Model Protocol.
|
| IndependentCascadeModelSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates a fixed number of own information pieces, and repropagates
pieces with a probability that only depends on the users receiving and propagating the information.
|
| IndependentCascadeModelSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selects the information pieces to propagate according to the independent cascade protocol, i.e.
|
| Index<C> |
Interface for a content index.
|
| Index<I> |
Generic index.
|
| IndexBuilder<C> |
Interface for an object that builds an index.
|
| IndexFeatureData<I> |
Class for loading feature data from an index.
|
| IndexReader<U> |
Interface for creating classes that read indexes.
|
| IndividualCommunityMetric<U> |
Computes a metric for each individual community.
|
| IndividualCommunityMetricGridSearch<U> |
Class for performing the grid search for a given individual community metric.
|
| IndividualCommunityMetricIdentifiers |
Identifiers for individual community metrics.
|
| IndividualCommunityMetricSelector<U> |
Class that translates from a grid to the different individual community metrics.
|
| IndividualContentIndex<C,U> |
Index that stores individual pieces for each user.
|
| IndividualContentIndexBuilder<C,U> |
Individual content index builder.
|
| IndividualSampler<U> |
Obtains a sample of users starting from a single user.
|
| IndividualSamplerFunction<U> |
Functions for obtaining an sampling approach that, given a user, selects
a group of candidate links for the prediction.
|
| IndividualSamplingAlgorithmConfigurator<U> |
Definition of the classes for obtaining the parameters for different sampling approaches.
|
| IndividualSamplingAlgorithmGridReader |
Reads the grid for sampling algorithms from a YAML file.
|
| IndividualSamplingAlgorithmGridSelector<U> |
Given a grid, this class obtains a sampling algorithm, to apply to every target user for a
link prediction / contact recommendation approach.
|
| IndividualSamplingAlgorithmIdentifiers |
Identifiers for the different sampling approaches in the library.
|
| IndividualSightMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Abstract implementation of a sight mechanism who values whether an information piece is observed by a user or not
independently.
|
| IndividualSimulationMetric<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for the different individual metrics (can be applied over individual
users) to apply over the simulation.
|
| InexistentEdgeException |
An edge metric could not be computed since the edge does not exist.
|
| InfiniteDistancePairsGridSearch<U> |
Grid for the number of infinite-distance pairs in the graph.
|
| InfiniteDistances<U> |
Finds the number of infinite distance pairs of nodes.
|
| InfiniteTimeExpirationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an expiration mechanism that never discards a piece.
|
| InfiniteTimeExpirationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Expiration mechanism that does not discard any information piece.
|
| InfoFeatureDistributionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a distribution measuring the number of times each information pieces feature has been received.
|
| Infomap<U extends java.io.Serializable> |
Community detection algorithm using the Infomap algorithm.
|
| InfomapConfigurator<U extends java.io.Serializable> |
Configurator for the Infomap community detection algorithm.
|
| InfoPiecesDistribution<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Distribution for information pieces.
|
| InfoPiecesDistributionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a distribution measuring the number of times each information piece has been received.
|
| Information<I> |
Piece of information.
|
| InformationCount<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Computes the number of information pieces received by each user in the network.
|
| InformationCountConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the average number of pieces received by each user.
|
| InformationFeatureDistribution<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Distribution for information pieces features.
|
| InformationFeatureSelectionFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Filters a list of information piece features, given by its identifier.
|
| InformationFeatureSelectionFilterConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for configuring a filter which keeps only a fraction of the item features in a given set, and
all the information pieces containing such features.
|
| InformationGiniComplementConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures how balanced the distribution of times each information piece has been received is.
|
| InformationPieceGiniComplement<U extends java.io.Serializable,I extends java.io.Serializable,P> |
It finds the complement of the Gini coefficient of the distribution of the times each information piece is received and seen
during the simulation.
|
| InformationPieceIndexGenerator |
Class for generating a context index.
|
| Instance<U> |
Machine learning individual pattern.
|
| InstancePostfixExLinkPredictor<U> |
Given as set of instances, this algorithm predicts the presence or absence of a link, according
to a function of the different features.
|
| InstanceSet<U> |
Class that represents a machine learning dataset for link prediction / contact
recommendation.
|
| InstanceSetCombiner<U> |
Auxiliar class for combining instance set in different manners.
|
| InstanceSetReader<U> |
Interface for reading an instance set for link prediction / contact recommendation.
|
| InstanceSetWriter<U> |
Class for writing patterns in different formats.
|
| InterCommunityDegreeGini<U> |
Computes the community degree Gini of the graph, i.e.
|
| InterCommunityDegreeGiniComplement<U> |
Implementation of a global reranking strategy for balancing the distribution of the degrees of the communities
in a community graph.
|
| InterCommunityDegreeGiniComplement<U> |
Implementation of a reranking strategy for balancing the distribution of the degrees of the communities
in a community graph.
|
| InterCommunityDegreeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| InterCommunityDegreeGiniComplement<U> |
Implementation of a reranking strategy for balancing the distribution of the degrees of the communities
in a community graph.
|
| InterCommunityDegreeGiniGridSearch<U> |
Grid for the inter-community degree Gini of the graph.
|
| InterCommunityDegreeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the degrees of the communities (restricted
to links between communities).
|
| InterCommunityEdgeGini<U> |
Computes the community edge Gini of the graph, i.e.
|
| InterCommunityEdgeGiniComplement<U> |
Implementation of a global reranking strategy for balancing the distribution of edges between pairs
of communities.
|
| InterCommunityEdgeGiniComplement<U> |
Implementation of a reranking strategy for balancing the distribution of edges between pairs
of communities.
|
| InterCommunityEdgeGiniComplement<U> |
Swap reranker that optimizes the Gini index of the distribution of edges between communities.
|
| InterCommunityEdgeGiniComplement<U> |
Reranks a recommendation by improving the Gini Index of the pairs of
different communities in a community graph.
|
| InterCommunityEdgeGiniGridSearch<U> |
Grid for the inter-community edge gini of the graph.
|
| InterCommunityEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| InterCommunityGraphGenerator<U> |
Generates a multi-graph which contains all communities as nodes and all links between
different communities as edges.
|
| InterCommunityOuterDegreeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the degrees of the communities (restricted
to links between communities).
|
| InterCommunityOuterEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| InterCommunityReranker<U> |
Global reranker for computing metrics that only use links between pairs of communities.
|
| InterCommunityReranker<U> |
Global reranker for computing metrics that only use links between pairs of communities.
|
| InterCommunityReranker<U> |
Reranker that uses community metrics of the user graph.
|
| InterEdgeGini<U> |
Computes the value for Gini for the different pairs of different nodes.
|
| InterEdgeGiniGridSearch<U> |
Grid for the edge Gini complement between different nodes in a graph.
|
| IntraListDiversityConfigurator<U,F> |
Grid search generator for the intra-list diversity metric.
|
| InverseCommunitySize<U> |
Implementation of a reranker which promotes recommending links in small communities.
|
| InverseCommunitySize<U> |
Implementation of a reranker which promotes recommending links in small communities.
|
| InverseCommunitySizeReranker<U> |
Implementation of a reranker which promotes recommending links in small communities.
|
| InverseDegree<U> |
Computes the inverse of the degree of a node.
|
| InverseDegreeGridSearch<U> |
Grid for the inverse degree of a node.
|
| InverseEdgeMetricReranker<U> |
Global reranker strategy that minimizes the average value of an edge metric.
|
| InverseGraphMetricReranker<U> |
Global reranker strategy that reorders the candidate users for minimizing a graph metric.
|
| InverseGraphMetricReranker<U> |
Reranker strategy that reorders the candidate users for minimizing a graph metric.
|
| InverseGraphMetricReranker<U> |
Individual reranker, which reorders a recommendation to demote
a graph metric.
|
| ItemBasedCFGridSearch<U> |
Grid search generator for item-based kNN collaborative filtering algorithm.
|
| ItemNoveltyMetric<U,I> |
Item novelty metric.
|
| Iteration<U,I,P> |
Class that represents a single iteration.
|
| IteratorsAbstractFastUpdateablePreferenceData<U,I> |
Extends AbstractFastUpdateablePreferenceData and implements the data access stream-based methods using the iterator-based ones.
|
| Jaccard<U> |
Recommended based on the Jaccard similarity.
|
| JaccardGridSearch<U> |
Grid search generator for Jaccard algorithm.
|
| JaccardSimilarity |
Similarity based on the Jaccard similarity link prediction algorithm
|
| JungGraph<U> |
JUNG graph Wrapper.
|
| Katz<U> |
Katz algorithm.
|
| KatzCentrality<U> |
Finds the Katz centrality of the nodes, which estimates the importance of a node considering the
paths between the node and the rest of the network.
|
| KatzCentralityGridSearch<U> |
Grid for the Katz centrality of a node.
|
| KatzGridSearch<U> |
Grid search generator for Katz algorithm.
|
| KLDivergence |
Computes the KL divergence as a distance between two distributions (an original one, P(x), and an estimated
one from real data Q(x).
|
| KMeans |
Implementation of the k-means clustering algorithm.
|
| LabelPropagation<U> |
Implementation of the label propagation algorithm.
|
| LabelPropagationConfigurator<U extends java.io.Serializable> |
Configures the label propagation community detection algorithm.
|
| LambdaMARTGridSearch<U> |
Grid search generator for LambdaMART algorithm.
|
| LambdaMARTJForestsRecommender<U> |
Class for applying the LambdaMART algorithm.
|
| LambdaMARTRecommender<U> |
Class that transforms the output of the JForest package to a recommendation
Note: it has to be executed outside.
|
| LambdaReranker<U,I> |
Linear combination re-ranker that combines the original score of the input
recommendation and a novelty component.
|
| LeadingVector<U> |
Class for computing the community partition using the Leading Vector algorithm.
|
| LETORFormatConstants |
Constant formats for learning to rank files.
|
| LETORInstanceReader<U> |
Class for reading the different patterns for ML algorithms as contact
recommendation / link prediction algorithms, using the LETOR
format.
|
| LETORInstanceWriter<U> |
Class for writing patterns in the LETOR format (for Learning TO Rank task).
|
| LimitedCountThresholdSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates a fixed number of own information pieces, and repropagates
a fixed number of pieces, chosen from those who have been received (at least) a number of times.
|
| LimitedCountThresholdSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selection mechanism that only propagates those received pieces which have been received (at least) a fixed
number of times.
|
| LimitedProportionThresholdSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates a fixed number of own information pieces, and repropagates
a fixed number of pieces, chosen from those who have been received (at least) from a fraction of his neighbors.
|
| LimitedProportionThresholdSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selection mechanism that only propagates those received pieces which have been received (at least) a fixed
number of times.
|
| LinkPredFastFilters<U> |
Filters for link prediction algorithms.
|
| LinkPrediction |
Class for executing and evaluating link prediction approaches.
|
| LinkPredictionFormat<U> |
Recommendation writers and readers with a common format.
|
| LinkPredictionFormat.Reader<U> |
Recommendation reader.
|
| LinkPredictionFormat.Writer<U> |
Link prediction writer.
|
| LinkPredictionMetric<U> |
Interface for defining metrics for evaluating link prediction algorithms.
|
| LinkPredictionMetricConfigurationsReader |
Class for reading contact recommendation metrics.
|
| LinkPredictionMetricConfigurator<U,F> |
Class for configuring a given link prediction metric.
|
| LinkPredictionMetricFunction<U,F> |
Functions for retrieving a configured link prediction metric.
|
| LinkPredictionMetricGridReader |
Class for reading contact recommendation metrics..
|
| LinkPredictionMetricGridSelector<U,F> |
Class that translates from a grid to different link prediction metrics.
|
| LinkPredictionMetricIdentifiers |
Identifiers for the different contact recommendation metrics
available in the library.
|
| LinkPredictionMetricParametersReader |
Class for reading contact recommendation metrics.
|
| LinkPredictionSampler<U> |
Samples all the links created in a test graph,
and the same amount of links which have not been created.
|
| LinkPredictionSamplerConfigurator<U> |
Class for configuring a sampling approach which takes all nodes.
|
| LinkPredictor<U> |
Definition of a method that predicts a collection of links which are likely
to appear in a social network in the future.
|
| LocalClusteringCoefficient<U> |
Computes the local clustering coefficient of a node.
|
| LocalClusteringCoefficientGridSearch<U> |
Grid for the local clustering coefficient of a node.
|
| LocalGreedyReranker<U,I> |
Generalization of greedy local reranking strategies, for processing several recommendations at a time.
|
| LocalLambdaReranker<U,I> |
Generalization of local greedy reranking strategies, for processing several recommendations at a time.
|
| LocalLHNIndex<U> |
Recommender that uses the local Leicht-Holme-Newman index.
|
| LocalLHNIndexGridSearch<U> |
Grid search generator for the local Leicht-Holme-Newman algorithm.
|
| LocalPathIndex<U> |
Local path index recommender.
|
| LocalPathIndexGridSearch<U> |
Grid search generator for Local Path Index algorithm.
|
| LocalRandomReranker<U,I> |
Random reranker.
|
| LocalReciprocityRate<U> |
Computes the local reciprocity rate, i.e.
|
| LocalReciprocityRateGridSearch<U> |
Grid for the reciprocity of a node.
|
| LocalReranker<U,I> |
Generalization of local reranking strategies, for processing several recommendations at a time.
|
| LogisticRegressionClassifier<U> |
Classifier that applies a logistic regression (i.e.
|
| LongTailNoveltyConfigurator<U,F> |
Grid search generator for the long tail novelty of the recommendations.
|
| LooseTimestampBasedSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates the information created by a user when the timestamp of the simulation
is equivalent to the real propagation timestamp.
|
| LooseTimestampBasedSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selection mechanism that takes the real timestamps of the users into account.
|
| Louvain<U extends java.io.Serializable> |
Class for computing the Louvain community detection algorithm.
|
| LouvainConfigurator<U extends java.io.Serializable> |
Configurator for the Louvain community detection algorithm.
|
| Love<U> |
Twitter Love algorithm.
|
| LoveGridSearch<U> |
Grid search generator for the Love algorithm.
|
| LTN<U,I> |
Global version of the long tail novelty.
|
| LuceneBuilder<C> |
Lucene implementation of an Index Builder
|
| LuceneForwardIndex<C> |
Lucene implementation of a forward index.
|
| LuceneForwardIndexBuilder<C> |
Lucene implementation of a builder for a forward index.
|
| LuceneFreqVector |
Lucene implementation of a term vector.
|
| LuceneFreqVectorIterator |
Iterator for the Lucene frequency vector
|
| LuceneIndex<C> |
Lucene implementation of an index.
|
| LucenePositionalIndex<C> |
Lucene implementation of a positional index.
|
| LucenePositionalIndexBuilder<C> |
Constructor for a Lucene positional index builder.
|
| LucenePositionalPostingsIterator |
Iterator for running over a Lucene positional posting list.
|
| LucenePositionalPostingsList |
Positional posting list for Lucene.
|
| LucenePostingsIterator |
Iterator of a Lucene posting list.
|
| LucenePostingsList |
Lucene posting list.
|
| LuceneTermFreq |
Lucene implementation of the TermFreq object.
|
| LuceneTfIdfFeaturesReader |
Class that loads tf-idf features from a content index.
|
| MachineLearningRecommender<U> |
Contact recommendation algorithm that uses supervised classification techniques to generate the
recommendation.
|
| MachineLearningWekaRecommender<U> |
Contact recommendation algorithm that uses supervised classification techniques to generate the
recommendation.
|
| Main |
Class for applying the main methods to the executions.
|
| MAPConfigurator<U,F> |
Grid search generator for the mean average precision (MAP) metric.
|
| MathFunctions |
Mathematical functions.
|
| MatrixBasedRecommender<U> |
Abstract implementation of a contact recommendation algorithm that depends on matrix operations.
|
| MatrixBasedVertexMetric<U> |
Vertex metric based on matrices.
|
| MatrixChecker |
Checks whether we can use the JBLAS library, or we have to use the COLT one
to perform matrix-based recommendations.
|
| MatrixForest<U> |
Implementation of the matrix forest algorithm for contact recommendation.
|
| MatrixForestGridSearch<U> |
Grid search generator for Matrix Forest algorithm.
|
| MatrixLibrary |
Enumeration for identifying the matrix libraries.
|
| MaximumCosineSimilarity<U> |
Recommender.
|
| MaxTimestampStopCondition<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Stop condition that determines a maximum possible timestamp for the execution.
|
| MaxTimestampStopConditionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a stop condition that establishes a maximum timestamp value.
|
| MeanPredictionDistance<U> |
Metric that finds the harmonic mean of the reciprocal distances between the different target user - candidate user pairs
of the recommendation.
|
| MeanPredictionDistanceConfigurator<U,F> |
Grid search generator for the mean prediction distance of the recommendations.
|
| MergerUpdateConfigurator |
Configures an update mechanism that updates the information in the newest piece with the older ones.
|
| MergerUpdateMechanism |
Updates the previously received elements with information obtained from the new ones.
|
| MetricConfigurationsReader |
Class for reading social network analysis metrics.
|
| MetricConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for the configuration of an information diffusion metric.
|
| MetricGridReader |
Class for reading social network analysis metrics.
|
| MetricIdentifiers |
The list of identifiers for the information diffusion metrics available.
|
| MetricParameterReader |
Class for reading the parameters for a diffusion metric.
|
| MetricParametersReader |
Class for reading social network analysis metrics.
|
| MetricSelector<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Class for selecting an individual diffusion metric.
|
| MetricTypeIdentifiers |
Identifiers for the different metric types.
|
| MFGraphUpdateableRecommender<U> |
Matrix factorization recommender.
|
| MFUpdateableRecommender<U,I> |
Matrix factorization recommender.
|
| MinimumFrequencyInformationFeatureFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Filter that removes any information feature that appears less than a fixed
number of times (i.e.
|
| MinimumFrequencyInformationFeatureFilterConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for configuring a filter which keeps only the information pieces feature available, at least,
in a minimum number of information pieces.
|
| MinMaxNormalizer<I> |
Min-max normalizer.
|
| MixedFeatureDistribution<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Distribution combining user and information pieces features.
|
| MixedParamDistributionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for configuring a distribution of two mixed parameters (one from information pieces,
and other from users).
|
| MLComparators<U> |
Comparators for ordering the link prediction algorithms.
|
| MLConstants |
Constants for Machine Learning algorithms.
|
| MLFeatureGenerator |
Class for generating learning to rank / machine learning examples.
|
| Modularity<U> |
Computes the modularity of a graph, given the communities.
|
| ModularityComplement<U> |
Implementation of a reranker which promotes the modularity complement of the network.
|
| ModularityComplement<U> |
Computes the modularity complement of a graph, given the communities.
|
| ModularityComplementGridSearch<U> |
Grid for the modularity complement of the graph.
|
| ModularityGridSearch<U> |
Grid for the modularity of the graph.
|
| Money<U> |
Twitter Money algorithm.
|
| MoneyGridSearch<U> |
Grid search generator for the Money algorithm.
|
| MonteCarloGini |
Gini coefficient of a random distribution
|
| MonteCarloGiniCollection |
Configures a set of MonteCarlo-computed Gini coefficients.
|
| MostCommonNeighbors<U> |
Recommended that sorts candidate users according to the number of neighbors in common with the target one.
|
| MostCommonNeighborsGridSearch<U> |
Grid search generator for Most Common Neighbors algorithm.
|
| MostCommonNeighborsSimilarity |
Similarity based on the Most Common Neighbors link prediction algorithm.
|
| MultiEdges |
Interface that represents the edges of a graph.
|
| MultiEdgeTypes |
Class that represents the type of the multiedges.
|
| MultiEdgeWeights |
Class that represents the weight of the edges.
|
| MultiGraph<U> |
Interface for representing multigraphs
|
| NaiveBayesClassifier<U> |
Classifier which applies the Naive Bayes method.
|
| NDCGConfigurator<U,F> |
Grid search generator for the normalized discounted cumulative gain (nDCG) metric.
|
| NeighbourOverlap<U> |
Computes the intersection between the neighborhoods of two nodes.
|
| NewestUpdateConfigurator |
Configures an update mechanism that just takes the newest piece.
|
| NewestUpdateMechanism |
Update mechanism for the information cascade model.
|
| NodeBetweenness<U> |
Computes the betweenness of the nodes of a graph.
|
| NodeBetweennessGridSearch<U> |
Grid for the betweenness of a node.
|
| NoIndexException |
Exception for the case when an index does not exist
|
| NoLinksGraphGenerator<U> |
Class for generating graphs without links.
|
| NominalStats |
Statistics values for nominal features.
|
| NoMoreNewPropagatedInfoStopCondition<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Uses as the end of the simulation the fact that no information has been seen by users in the last
iteration.
|
| NoMoreNewStopConditionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an stop condition that establishes that the diffusion ends when no new information is propagated.
|
| NoMorePropagatedInfoStopCondition<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Uses as the end of the simulation the fact that no information has been propagated in the last
iteration.
|
| NoMorePropagatedStopConditionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an stop condition that establishes that the diffusion ends when no more information is propagated.
|
| NoMoreTimestampsNorPropInfoStopCondition<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Stop condition: When the last timestamp has appeared, then, stop.
|
| NoMoreTimestampsNorPropInfoStopConditionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an stop condition that finishes the diffusion procedure as it reaches the timestamp of the
last propagated information piece (according to the diffusion timestamps of a real procedure), and no
more information is propagated.
|
| NoMoreTimestampsStopCondition<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Stop condition: when the last timestamp has appeared, then, stop.
|
| NoMoreTimestampsStopConditionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an stop condition that finishes the diffusion procedure as it reaches the timestamp of the
last propagated information piece (according to the diffusion timestamps of a real procedure).
|
| NoNormalizer<I> |
Normalizer that does not transform the data at all.
|
| NonReciprocalPreferentialAttachment<U> |
Non Reciprocal Preferential Attachment recommender.
|
| NormalizedCutSpectralClustering<U> |
Community detection algorithm for balanced communities.
|
| NormalizedCutSpectralClusteringConfigurator<U extends java.io.Serializable> |
Configurator for the Spectral Clustering community detection based on minimizing
the normalized cut.
|
| Normalizer<I> |
Interface for normalization.
|
| Normalizers |
Examples of normalizers.
|
| NumCommunities<U> |
Metric that finds the number of communities of a graph.
|
| NumCommunitiesGridSearch<U> |
Grid search for the metric that finds the number of communities in a graph.
|
| NumEdges<U> |
Computes the number of edges in the graph.
|
| NumEdgesGridSearch<U> |
Grid for the number of edges of the graph.
|
| NumInformationPiecesFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Filter that limits the maximum number of information pieces that a single user
can have.
|
| NumInformationPiecesFilterConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures filter which only leaves a fixed number of information pieces for each user to
propagate.
|
| NumIterStopCondition<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Stops after a given number of iterations.
|
| NumIterStopConditionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an stop condition that finishes the diffusion procedure after a fixed number of iterations.
|
| OldestUpdateConfigurator |
Configures an update mechanism that just takes the newest piece.
|
| OldestUpdateMechanism |
Update mechanism that just takes the oldest information piece.
|
| OnlyOwnInformationSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selection mechanism that does not propagate any information piece created by other users (only
pieces owned by the propagating user).
|
| OnlyOwnSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that only propagates the information created by the user.
|
| OnlyRepropagatedPiecesFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Filter that removes information pieces that are not propagated by other users.
|
| OnlyRepropagatedPiecesFilterConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a filter which keeps only those pieces which have been repropagated in a real setting.
|
| OrderedListCombiner |
Methods and algorithms for combining ordered lists.
|
| OriginalDirectEdgeMetricReranker<U> |
Reranker strategy that optimizes the average value of an edge metric.
|
| OriginalDirectEdgeMetricReranker<U> |
Reranker that optimizes the average value of an edge metric.
|
| OriginalDirectUserMetricReranker<U> |
Global reranker that optimizes the average value of vertex metric.
|
| OriginalDirectUserMetricReranker<U> |
Reranker that optimizes the average value of vertex metric.
|
| OriginalDirectUserMetricReranker<U> |
Reranker that optimizes the average value of vertex metric.
|
| OriginalInverseEdgeMetricReranker<U> |
Reranker strategy that minimizes the average value of an edge metric.
|
| OriginalInverseEdgeMetricReranker<U> |
Reranker that minimizes the average value of an edge metric.
|
| OriginalInverseUserMetricReranker<U> |
Global reranker that minimizes the average value of vertex metric.
|
| OriginalInverseUserMetricReranker<U> |
Reranker that minimizes the average value of vertex metric.
|
| OriginalInverseUserMetricReranker<U> |
Reranker that minimizes the average value of vertex metric.
|
| OuterAlternativeSemiCompleteCommunityEdgeGiniComplement<U> |
Swap reranker that optimizes the Gini index of the distribution of edges between communities.
|
| OuterCompleteCommunityDegreeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| OuterCompleteCommunityEdgeGiniComplement<U> |
Swap reranker that optimizes the Gini index of the distribution of edges between communities.
|
| OuterInterCommunityDegreeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| OuterInterCommunityEdgeGiniComplement<U> |
Swap reranker that optimizes the Gini index of the distribution of edges between communities.
|
| OuterSemiCompleteCommunityEdgeGiniComplement<U> |
Swap reranker that optimizes the Gini index of the distribution of edges between communities.
|
| OuterSizeNormalizedCompleteCommunityDegreeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| OuterSizeNormalizedCompleteCommunityEdgeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| OuterSizeNormalizedInterCommunityDegreeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| OuterSizeNormalizedInterCommunityEdgeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| OuterSizeNormalizedSemiCompleteCommunityEdgeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| PageRank<U> |
Recommends an user by her PageRank score.
|
| PageRank<U> |
Computes the PageRank values of the different nodes in the graph.
|
| PageRankGridSearch<U> |
Grid search generator for PageRank algorithm.
|
| PageRankGridSearch<U> |
Grid for the PageRank value of a node.
|
| PageRankHittingTime<U> |
Implementation of the Hitting time (using the not-personalized
PageRank transition matrix)
|
| Pair<U> |
Class that represents a pair of objects of the same type.
|
| PairMetric<U> |
Interface for node pair based metrics.
|
| PairMetricFunction<U> |
Functional interface for obtaining pair metrics.
|
| PairMetricGridSearch<U> |
Class for performing the grid search for a metric for a pair of nodes.
|
| PairMetricIdentifiers |
Identifiers for metrics for pairs of users in the network.
|
| PairMetricSelector<U> |
Class that translates from a grid to the different pair metrics.
|
| PairMetricsTest |
Automated unit tests for metrics computed over pairs of users.
|
| PajekGraphReader<U extends java.io.Serializable> |
Reads a graph using the Pajek format:
|
| PajekGraphWriter<U extends java.io.Serializable> |
Writes the graph in the Pajek format.
|
| Parameters |
Class for storing the configuration parameters for an algorithm, metric, etc.
|
| ParametersReader |
Class for reading parameters from a YAML file.
|
| PatternReader<U,S,I> |
Class for reading machine learning patterns.
|
| PearsonCorrelation<U> |
Class for computing the Pearson correlation of scalar values for a graph.
|
| PersonalizedHITS<U> |
Personalized version of the HITS recommender.
|
| PersonalizedHITSGridSearch<U> |
Grid search generator for the personalized HITS algorithm.
|
| PersonalizedPageRank<U> |
Recommends an user by her personalized PageRank score.
|
| PersonalizedPageRankGridSearch<U> |
Grid search generator for personalized PageRank algorithm.
|
| PersonalizedPageRankHittingTime<U> |
Implementation of the Hitting time (using the personalized
PageRank transition matrix)
|
| PersonalizedSALSA<U> |
General personalized SALSA recommender.
|
| PersonalizedSALSAGridSearch<U> |
Grid search generator for personalized SALSA algorithm.
|
| PivotedNormalizationVSM<U> |
Adaptation of the pivoted normalization vector space model (VSM).
|
| PivotedNormalizationVSMGridSearch<U> |
Grid search generator for the PL2 Divergence from Randomness method
|
| PL2<U> |
Class that applies the PL2 Divergence from Randomness model as a contact
recommendation algorithm.
|
| PL2GridSearch<U> |
Grid search generator for the PL2 Divergence from Randomness method
|
| PL2Similarity |
Similarity based on the PL2 model from Information Retrieval
|
| PMFFactorizerBasic<U,I> |
Factorizer for the probabilistic matrix factorization algorithm (PMF).
|
| PMFFactorizerSigmoid<U,I> |
Factorizer for the sigmoid version of the probabilistic matrix factorization algorithm (PMF).
|
| Popularity<U> |
Popularity recommender.
|
| PopularityGridSearch<U> |
Grid search generator for Popularity algorithm.
|
| PositionalPosting |
Positional posting implementation.
|
| PositionsIterator |
Iterator over a list of positions
|
| Posting |
Posting in an index.
|
| PostingsList |
Interface for posting lists
|
| Precision<U> |
Implementation of the precision metric for link prediction.
|
| PrecisionConfigurator<U,F> |
Grid search generator for the precision metric.
|
| PrecisionConfigurator<U,F> |
Grid search generator for the precision metric.
|
| Prediction<U> |
The result of applying a link prediction algorithm.
|
| PredictionGiniComplementConfigurator<U,F> |
Grid search generator for the predicted Gini complement of the recommendations.
|
| PreferentialAttachment<U> |
Recommender based on the preferential attachment phenomena.
|
| PreferentialAttachment<U> |
Preferential attachment value: finds the product of the degrees of the two users.
|
| PreferentialAttachmentGridSearch<U> |
Grid for the preferential attachment of a pair of users.
|
| ProgressiveDirectEdgeMetricReranker<U> |
Global reranker strategy that optimizes the average value of an edge metric.
|
| ProgressiveDirectEdgeMetricReranker<U> |
Reranker that optimizes the average value of an edge metric.
|
| ProgressiveDirectUserMetricReranker<U> |
Global reranker that optimizes the average value of vertex metric.
|
| ProgressiveDirectUserMetricReranker<U> |
Implementation of a reranking strategy for contact recommendation that promotes the
average value of some vertex metric in the resulting network.
|
| ProgressiveDirectUserMetricReranker<U> |
Implementation of a reranking strategy for contact recommendation that promotes the
average value of some vertex metric in the resulting network.
|
| ProgressiveInverseEdgeMetricReranker<U> |
Reranker strategy that minimizes the average value of an edge metric.
|
| ProgressiveInverseEdgeMetricReranker<U> |
Reranker that minimizes the average value of an edge metric.
|
| ProgressiveInverseUserMetricReranker<U> |
Global reranker that minimizes the average value of vertex metric.
|
| ProgressiveInverseUserMetricReranker<U> |
Implementation of a reranking strategy for contact recommendation that minimizes the
average value of some vertex metric in the resulting network.
|
| ProgressiveInverseUserMetricReranker<U> |
Implementation of a reranking strategy for contact recommendation that demotes the
average value of some vertex metric in the resulting network.
|
| PropagatedInformation |
Class that represents the propagated information in a simulation.
|
| PropagationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for configuring propagation mechanisms.
|
| PropagationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Mechanism for selecting the set of users towards whom each user in the network propagates his/her information
pieces.
|
| PropagationMechanismIdentifiers |
Identifiers for the different propagation mechanisms for information diffusion protocols available in
the framework.
|
| PropagationParameterReader |
Class for reading an propagation mechanism for information diffusion.
|
| PropagationSelector<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for selecting a propagation mechanism from its configuration.
|
| PropFlow<U> |
Recommender which uses the PropFlow algorithm.
|
| PropFlowGridSearch<U> |
Grid search generator for PropFlow algorithm.
|
| ProportionThresholdModelConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a protocol in which propagates the received information if a large enough fraction of neighbors send the same piece to him/her.
|
| ProportionThresholdModelProtocol<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Threshold model protocol.
|
| ProportionThresholdSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates a fixed number of own information pieces, and repropagates
pieces which have been received from (at least) a given proportion of the user neighbors.
|
| ProportionThresholdSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selection mechanism that only propagates those received pieces which have been received (at least) a fixed
number of times.
|
| Protocol<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Information propagation protocol.
|
| ProtocolConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for configuring protocols for information diffusion, given their properties.
|
| ProtocolIdentifiers |
Identifiers for the different preconfigured propagation protocols which are available
in the library.
|
| ProtocolParameterReader |
Reads the parameters for diffusion protocols.
|
| ProtocolSelector<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for selecting a suitable information diffusion protocol from its configuration.
|
| ProtocolType |
Enumeration describing the possible names for the information propagation protocols.
|
| PseudoInverseCosine<U> |
Implementation of the pseudo inverse cosine algorithm for contact recommendation.
|
| PseudoInverseCosineGridSearch<U> |
Grid search generator for pseudo-inverse cosine algorithm.
|
| PullModelConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures the pull model protocol.
|
| PullModelProtocol<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Protocol that applies the push strategy for diffunding the information.
|
| PullPropagationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a pull propagation mechanism.
|
| PullPushPropagationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a push-pull propagation mechanism.
|
| PullPushPureRecommenderPropagationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a push-pull propagation mechanism.
|
| PullPushRecommenderPropagationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a push-pull propagation mechanism.
|
| PullPushSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a pure push-pull selection mechanism, where all the previously known information by the users
is propagated.
|
| PullPushSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selection mechanism following the original one proposed by the push, pull and push-pull models: all the known information
(i.e.
|
| PullPushStrategyPropagationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Propagation mechanism for the so-called rumour spreading propagation mechanism.
|
| PullPushStrategyPureRecommenderPropagationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Propagation mechanism for the so-called rumour spreading propagation mechanism.
|
| PullPushStrategyRecommenderPropagationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Propagation mechanism for the so-called rumour spreading propagation mechanism.
|
| PullStrategyPropagationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Propagation mechanism that follows the pull strategy propagation mechanism.
|
| PurePersonalizedPageRank<U> |
Recommender algorithm based in a modified Personalized PageRank.
|
| PureRecommenderSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates a fixed number of own information pieces, and repropagates
pieces which have been received through recommended links.
|
| PureRecommenderSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selects information pieces to propagate depending on the original users and whether they have been propagated through
recommended links.
|
| PureTimestampBasedSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that only propagates and repropagates information
when the timestamp of the simulation corresponds to the real one.
|
| PureTimestampBasedSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selection mechanism that takes the real timestamps of the users into account.
|
| PushModelConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures the push model protocol.
|
| PushModelProtocol<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Model that applies the push strategy for diffunding the information.
|
| PushPropagationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a push propagation mechanism.
|
| PushStrategyPropagationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Propagation mechanism that follows the push strategy propagation mechanism.
|
| QLD<U> |
Adaptation of the Query Likelihood Information Retrieval method, with Dirichlet regularization.
|
| QLDGridSearch<U> |
Grid search generator for Query Likelihood algorithm with Dirichlet smoothing.
|
| QLDSimilarity |
Similarity based on the Query Likelihood IR model with Dirichlet smoothing.
|
| QLJM<U> |
Adaptation of the Query Likelihood Information Retrieval method, with Jelinek-Mercer regularization.
|
| QLJMGridSearch<U> |
Grid search generator for Query Likelihood algorithm with Jelinek-Mercer smoothing.
|
| QLJMSimilarity |
Similarity based on the Query Likelihood IR model with Jelinek-Mercer smoothing.
|
| QLL<U> |
Adaptation of the Query Likelihood Information Retrieval method, with Laplace regularization.
|
| QLLGridSearch<U> |
Grid search generator for Query Likelihood algorithm with Laplace smoothing.
|
| QLLSimilarity |
Similarity based on the Query Likelihood IR model with Laplace smoothing.
|
| Radius<U> |
Computes the radius of a network.
|
| RadiusGridSearch<U> |
Grid for the radius of the graph.
|
| Random<U> |
Recommends users randomly.
|
| RandomFiller<U,I> |
Filler that completes ranking with random recommendation.
|
| RandomGraphGenerator |
Program for generating random graphs.
|
| RandomGridSearch<U> |
Grid search generator for Random algorithm.
|
| RandomRerankerGridSearch<U> |
Grid search for a random reranker.
|
| RanksimNormalizer<I> |
Ranksim normalizer.
|
| RatioCutSpectralClustering<U> |
Community detection algorithm for balanced communities.
|
| RatioCutSpectralClusteringConfigurator<U extends java.io.Serializable> |
Configurator for the Spectral Clustering community detection based on minimizing
the ratio cut.
|
| RealPropagatedGlobalRecall<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Computes the fraction of pieces which were repropagated in the real setting which have been received by the users.
|
| RealPropagatedGlobalRecallConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the fraction of the pieces propagated in a real process which
have been received.
|
| RealPropagatedIndividualRecallConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the fraction of the pieces propagated in a real process which
have been received (individually for each user).
|
| RealPropagatedRecall<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Computes the fraction of pieces which were repropagated in the real setting which have been received by each user.
|
| Recall<U> |
Implementation of the recall metric for link prediction.
|
| RecallConfigurator<U,F> |
Grid search generator for the recall metric.
|
| RecallConfigurator<U,F> |
Grid search generator for the recall metric.
|
| ReciprocalAverageEccentricity<U> |
Computes the diameter of a network.
|
| ReciprocalAverageEccentricityGridSearch<U> |
Grid for the reciprocal average eccentricity of the graph.
|
| ReciprocalDiameter<U> |
Computes the reciprocal diameter of a network.
|
| ReciprocalDiameterGridSearch<U> |
Grid for the reciprocal diameter of the graph.
|
| ReciprocalLinks<U> |
Recommends reciprocal links.
|
| ReciprocalShortestPathLength<U> |
Computes the Reciprocal Shortest Path Length.
|
| ReciprocalShortestPathLengthGridSearch<U> |
Grid search for the Reciprocal Shortest Path Length metric.
|
| ReciprocityRate<U> |
Reciprocity rate of the graph (proportion of reciprocal links)
|
| ReciprocityRate<U> |
Checks if a graph has the reciprocal edge of a pair.
|
| ReciprocityRateGridSearch<U> |
Grid for the reciprocity rate of the graph.
|
| ReciprocityRateGridSearch<U> |
Grid search for the reciprocity of a pair of nodes.
|
| Recommendation |
Class for recommending and evaluating contact recommendation approaches.
|
| RecommendationAlgorithmFunction<U> |
Functions for retrieving trained recommendation algorithms.
|
| RecommendationLinkPredictor<U> |
Link prediction algorithm based on a contact recommendation algorithm.
|
| RecommendationMetricFunction<U,F> |
Functions for retrieving a configured recommendation metric.
|
| RecommendedSightConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a sight mechanism that makes users observe pieces coming from recommended links with a certain probability
and pieces coming from the original network links with another.
|
| RecommendedSightMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
This mechanism applies two different probabilities: one for observing information
pieces from recommended users, and other for observing information pieces from
training users.
|
| RecommenderIndividualSampler<U> |
Samples the top k of a contact recommendation algorithm.
|
| RecommenderIndividualSamplerConfigurator<U> |
Class for configuring distance two individual samplers.
|
| RecommenderSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that propagates a fixed number of own information pieces, and repropagates
pieces which have been received through recommended links with a certain probability, and through not recommended
links with other.
|
| RecommenderSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selects the propagated pieces depending on the recommendations.
|
| RecommenderSimilarity |
Class which applies any contact recommendation algorithm as a graph
similarity for contact recommendation / link prediction.
|
| RecommenderSupplier<U> |
Interface for obtaining a configured contact recommendation algorithm.
|
| RecommenderTest |
Automated unit tests for checking some recommendation approaches.
|
| RecommMetricConfigurationsReader |
Class for reading contact recommendation metrics.
|
| RecommMetricConfigurator<U,F> |
Class for configuring a given recommendation metric.
|
| RecommMetricGridReader |
Class for reading contact recommendation metrics..
|
| RecommMetricGridSelector<U,F> |
Class that translates from a grid to the different contact recommendation algorithms.
|
| RecommMetricIdentifiers |
Identifiers for the different contact recommendation metrics
available in the library.
|
| RecommMetricParametersReader |
Class for reading contact recommendation metrics.
|
| ReducedIndex<T> |
Index that cannot be modified.
|
| Relation<W> |
A relation between two different sets of objects.
|
| RelevantEdgesFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Filter that removes recommended and not relevant edges from the graph.
|
| RelevantEdgesFilterConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a filter which, if a recommendation has been added to the original graph, keeps only those relevant
recommended edges.
|
| RerankerConfigurationsReader |
Class for reading reranking algorithms.
|
| RerankerGridReader |
Class for reading reranking algorithms.
|
| RerankerGridSearch<U> |
Interface for obtaining the different configurations of a given global reranking algorithm.
|
| RerankerGridSelector<U> |
Class that translates from a grid to the different contact recommendation algorithns.
|
| RerankerIdentifiers |
Identifiers for the different contact recommendation algorithms available in
the library
|
| RerankerParametersReader |
Class for reading reranking algorithms.
|
| Reranking |
Program for applying a given reranking algorithm to the outcome of a contact recommendation algorithm.
|
| ResourceAllocation<U> |
Recommender that uses the resource allocation principle to recommend.
|
| ResourceAllocationGridSearch<U> |
Grid search generator for resource allocation algorithm.
|
| ROCCurve<U> |
Given a list, finds the receiver operating characteristic (ROC) curve.
|
| RumorSpreadingModelConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a simple rumor spreading model protocol.
|
| RumorSpreadingModelProtocol<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Adaptation of the pull-push protocol.
|
| SALSA<U> |
Recommender system that uses SALSA Algorithm.
|
| SALSAGridSearch<U> |
Grid search generator for SALSA algorithm.
|
| Sampler<V> |
Interface for all the classes that generate subsamples from a graph.
|
| SearchEngine |
Interface defining the methods for a search engine.
|
| Selection |
Selection of information pieces to propagate.
|
| SelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for configuring a selection mechanism.
|
| SelectionConstants |
Constants for the selection mechanisms.
|
| SelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Interface for selecting, each iteration of a diffusion process, the set of users that might propagate
some information and the information pieces each one of them might propagate.
|
| SelectionMechanismIdentifiers |
List of identifiers of the selection mechanisms which are available in the framework.
|
| SelectionParameterReader |
Class for reading a selection mechanism for information diffusion.
|
| SelectionSelector<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class that selects an individual selection mechanism given its parameters.
|
| SemiCompleteCommunityEdgeGini<U> |
Computes the community edge Gini of the graph, i.e.
|
| SemiCompleteCommunityEdgeGiniComplement<U> |
Swap reranker that optimizes the Gini index of the distribution of edges between communities.
|
| SemiCompleteCommunityEdgeGiniGridSearch<U> |
Grid for the semi-complete community edge Gini of the graph.
|
| SemiCompleteCommunityEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| SemiCompleteCommunityOuterEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| SemiCompleteEdgeGini<U> |
Computes the value for Gini for the different pairs of nodes.
|
| SemiCompleteEdgeGiniGridSearch<U> |
Grid for the edge Gini between all pairs of nodes in a graph, considering selfloops in a separate
group.
|
| ShortestDistance<U> |
Recommends users by computing the distance between two of them.
|
| ShortestDistanceGridSearch<U> |
Grid search generator for the shortest distance algorithm.
|
| ShrinkingASL<U> |
Computes the variation of the average shortest path length if a link is
included in the graph.
|
| ShrinkingASLGridSearch<U> |
Grid for a metric that computes the reduction of the average shortest path
length in a network if a link is added.
|
| ShrinkingASLNeighbors<U> |
Computes the variation of the average shortest path length between the neighbors
of a pair of nodes if the link was added to the graph.
|
| ShrinkingASLNeighborsGridSearch<U> |
Grid for a metric that computes the reduction of the average shortest path
length in a network if a link is added.
|
| ShrinkingDiameter<U> |
Computes the variation of the diameter if a link is
included in the graph.
|
| ShrinkingDiameterGridSearch<U> |
Grid for a metric that computes the reduction of the diameter
in a network if a link is added.
|
| ShrinkingDiameterNeighbors<U> |
Computes the variation of the average shortest path length between the neighbors
of a pair of nodes if the link was added to the graph.
|
| ShrinkingDiameterNeighborsGridSearch<U> |
Grid for a metric that computes the reduction of the diameter in a network if a link is added.
|
| SightConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for configuring a sight mechanism from its parameter setting.
|
| SightMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Mechanism that decides which of the information pieces that a user has received are actually seen (payed attention to)
by each of the users in the network.
|
| SightMechanismIdentifiers |
List of identifiers of the different sight mechanisms available in the framework.
|
| SightParameterReader |
Class for reading a sight mechanism for information diffusion.
|
| SightSelector<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class that selects a sight mechanism from its parameter selection.
|
| SimpleCommunityGraphGenerator<U> |
Generates a community graph, which has, at most, a single link between
each pair of communities (including auto-loops).
|
| SimpleConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures simple diffusion protocol.
|
| SimpleFastUpdateableFeatureIndex<F> |
Simple implementation of FastUpdateableFeatureIndex backed by a bi-map IdxIndex
|
| SimpleFastUpdateableItemIndex<I> |
Simple implementation of FastUpdateableItemIndex backed by a bi-map IdxIndex
|
| SimpleFastUpdateablePreferenceData<U,I> |
Simple implementation of FastPreferenceData backed by nested lists.
|
| SimpleFastUpdateableUserIndex<U> |
Simple implementation of FastUpdateableUserIndex backed by a bi-map IdxIndex
|
| SimpleIteration<U,I,P> |
Class for storing the basic information of a simulation iteration.
|
| SimpleLinkPredictionFormat<U> |
Simple format for link prediction: tab-separated user-user-score triplets, by decreasing order of score.
|
| SimpleProtocol<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Simple simulator.
|
| Simulation<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Class that stores the evolution of a simulation over time.
|
| SimulationEdgeTypes |
Constants for edge types.
|
| SimulationMetric<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for the different metrics to apply over the simulation.
|
| SimulationMetricsParameterReader |
Obtains the configuration of metrics to use in the evaluation of the information diffusion process.
|
| SimulationMetricsSelector<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Class that selects an individual filter from a grid.
|
| SimulationParameterReader |
Reads a YAML file containing the configuration for simulating information diffusion.
|
| SimulationReader<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Interface for reading a simulation from a file.
|
| SimulationState<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Stores the current state of a simulation.
|
| SimulationWriter<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Interface for writing a simulation into a file.
|
| Simulator<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Class for the execution of information propagation simulations.
|
| SimulatorSelector<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class that selects a single simulator for a grid.
|
| Size<U> |
Computes the size of communities.
|
| SizeNormalizedCommunityDegreeGini<U> |
Computes the community degree Gini of the graph, i.e.
|
| SizeNormalizedCommunityEdgeGini<U> |
Computes the size normalized community edge Gini of the graph, i.e.
|
| SizeNormalizedCompleteCommunityDegreeGini<U> |
Computes the community degree Gini of the graph, i.e.
|
| SizeNormalizedCompleteCommunityDegreeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| SizeNormalizedCompleteCommunityDegreeGiniGridSearch<U> |
Grid for the size normalized complete degree Gini of the graph.
|
| SizeNormalizedCompleteCommunityEdgeGini<U> |
Computes the size normalized community edge Gini of the graph, i.e.
|
| SizeNormalizedCompleteCommunityEdgeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| SizeNormalizedCompleteCommunityEdgeGiniGridSearch<U> |
Grid for the size-normalized complete community edge Gini of the graph.
|
| SizeNormalizedInterCommunityDegreeGini<U> |
Computes the community degree Gini of the graph, i.e.
|
| SizeNormalizedInterCommunityDegreeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| SizeNormalizedInterCommunityDegreeGiniGridSearch<U> |
Grid for the size normalized inter-community degree Gini of the graph.
|
| SizeNormalizedInterCommunityEdgeGini<U> |
Computes the size normalized community edge Gini of the graph, i.e.
|
| SizeNormalizedInterCommunityEdgeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| SizeNormalizedInterCommunityEdgeGiniGridSearch<U> |
Grid for the size-normalized inter-community edge Gini of the graph.
|
| SizeNormalizedSemiCompleteCommunityEdgeGini<U> |
Computes the size normalized community edge Gini of the graph, i.e.
|
| SizeNormalizedSemiCompleteCommunityEdgeGiniComplement<U> |
Swap reranker for promoting the balance in the degree distribution for the different
communities.
|
| SizeNormalizedSemiCompleteCommunityEdgeGiniGridSearch<U> |
Grid for the size-normalized semi-complete community edge Gini of the graph.
|
| SizeNormCompleteCommunityDegreeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the degrees of the communities, normalized by its maximum possible value.
|
| SizeNormCompleteCommunityEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| SizeNormCompleteCommunityOuterDegreeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the degrees of the communities, normalized by its maximum possible value.
|
| SizeNormCompleteCommunityOuterEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| SizeNormInterCommunityDegreeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the degrees of the communities (restricted
to links between communities), normalized by the maximum possible value.
|
| SizeNormInterCommunityEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities (restricted
to nodes between communities).
|
| SizeNormInterCommunityOuterDegreeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the degrees of the communities (restricted
to links between communities), normalized by the maximum possible value.
|
| SizeNormInterCommunityOuterEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities (restricted
to nodes between communities).
|
| SizeNormSemiCompleteCommunityEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| SizeNormSemiCompleteCommunityOuterEdgeGiniRerankerGridSearch<U> |
Grid search for a reranker that reduces the Gini index of the number of links between pairs of communities.
|
| SizeWeightedFastGreedy<U> |
Alternative version of the Balanced Fast Greedy algorithm for optimizing modularity, and the size of communities, that
computes the whole dendogram for communities.
|
| SizeWeightedFastGreedyConfigurator<U extends java.io.Serializable> |
Configurator for the balanced version of the FastGreedy community detection algorithm
|
| SMOTEBalancer<U> |
Balances a dataset using the Synthetic Minority Over-Sampling Technique (SMOTE).
|
| SocialFastFilters |
Filters for contact recommendation.
|
| Sorensen<U> |
Recommender based on Sorensen similarity.
|
| SorensenGridSearch<U> |
Grid search generator for Sorensen index algorithm.
|
| SpecificItemSimilarity<I> |
Similarity between items.
|
| SpecificUserSimilarity<U> |
Similarity between users.
|
| SpectralClustering<U> |
Community detection algorithm for balanced communities.
|
| Speed<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Computes the number of different pieces of information propagated and seen in all the iterations.
|
| SpeedConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the speed of the diffusion.
|
| StatisticalSignificance |
Given some recommendations, computes the statistical significance between them.
|
| StatsBasedNormalizer<I> |
Normalizer based on the data statistics.
|
| StopCondition<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for defining stop conditions for simulations.
|
| StopConditionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for the configuration of stop conditions for information diffusion.
|
| StopConditionIdentifiers |
Identifiers for the different stop conditions for the simulation of information propagation
which are available in the framework.
|
| StopConditionParameterReader |
Class for reading a filter for information diffusion.
|
| StopConditionSelector<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Class for selecting an individual stop condition from a grid.
|
| StreamsAbstractFastUpdateablePreferenceData<U,I> |
Extends AbstractFastUpdateablePreferenceData and implements the data access iterator-based methods
using the stream-based ones.
|
| StronglyConnectedComponents<U> |
Computes communities via the Strongly Connected Components.
|
| StronglyConnectedComponentsConfigurator<U extends java.io.Serializable> |
Configurator for an algorithm that computes the strongly connected components of a graph.
|
| StrongTiesReranker<U> |
Reranker that promotes the number of links inside communities.
|
| StrongTiesRerankerGridSearch<U> |
Grid search for a reranker that increases the number of strong ties in the network.
|
| SubGraphGenerator<U> |
Generates a subgraph from another graph, containing only a selection of nodes.
|
| SupervisedLinkPredictor<U> |
A supervised link prediction method, based on Weka classifiers.
|
| SwapGreedyReranker<U,I> |
Abstract greedy implementation of the swap reranking strategy for optimizing global properties
of the system.
|
| SwapLambdaReranker<U,I> |
Abstract implementation of the greedy swap strategy that allows to optimize
at the same time the accuracy of the system (given by the original ranking) and the
global property we want to optimize.
|
| SwapReranker<U,I> |
Abstract implementation for a family of reranking strategies for optimizing a global
parameter of the recommendations (e.g.
|
| TemporalConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a temporal protocol, which replicates an old diffusion process.
|
| TemporalProtocol<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Simulation protocol that considers the timestamps.
|
| TermData<U,I> |
Posting information for a term in a content.
|
| TermFreq |
Element for storing a term and its frequency.
|
| TerrierIndex |
Class for generating Terrier indexes and queries from graphs.
|
| TerrierIRSimilarity |
Class that uses the Terrier IR engine to generate similarities between elements.
|
| TerrierRecommender<U> |
IR-based recommender models created using the Terrier library.
|
| TerrierStructure |
Structure for storing the different possible indexes and queries
for a Terrier index.
|
| TextCommunitiesReader<U> |
Reads a file containing the community structure.
|
| TextCommunitiesWriter<U> |
Writes a community file.
|
| TextGraphReader<V> |
Reads a graph from a file.
|
| TextGraphWriter<V> |
Writes a graph to a file.
|
| TextMultiGraphReader<V> |
Class that reads a multi-graph from a file.
|
| TextParser |
Interface for text parsers.
|
| TimedExpirationConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an expiration mechanism that discards all the pieces after a fixed time.
|
| TimedExpirationMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Expiration mechanism that discards information pieces after a certain number of iterations.
|
| TimestampBasedSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selection mechanism that takes the real timestamps of the users into account.
|
| TimestampOrderedSelectionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a selection mechanism that sorts the selection of information of each user to propagate by timestamp.
|
| TimestampOrderedSelectionMechanism<U extends java.io.Serializable,I extends java.io.Serializable,P> |
Selection mechanism that takes into account the real timestamp of the information pieces to propagate the information owned
by the user.
|
| ToLowerParser |
Simple text parser that converts a text into lower case.
|
| TotalNeighbors<U> |
Recommends people according to the total number of neighbors between the two users.
|
| TotalPropagatedStopCondition<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Stops after a given number of information pieces has been propagated.
|
| TotalPropagatedStopConditionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures an stop condition that finishes after a given amount of information pieces have been propagated.
|
| TransposedUpdateablePreferenceData<I,U> |
Updateable transposed preferences, where users and items change roles.
|
| TRECAveragePrecision<U,I> |
Average Precision: average of the precision at each recall level.
|
| Tree<U> |
Interface for managing and creating tree graphs.
|
| TreeCloneGenerator<U> |
Class for cloning trees.
|
| Triplet<X,Y,Z> |
Element that stores three different values.
|
| TukeyTestFileGenerator |
Given some recommendations, computes the statistical significance between them.
|
| Tuple2ol<U> |
Tuple that contains a long as second type.
|
| Tuple2oo<U,I> |
Class that represents a pair of objects of different type.
|
| TuplesLinkPredictionFormat<U> |
Format for writing the link predictions.
|
| TwitterAverageCosineSimilarity<U> |
Twitter average cosine: executes the average cosine over bipartite graphs from
the reduced graph.
|
| TwitterAverageCosineSimilarityGridSearch<U> |
Grid search generator for Twitter version of the average cosine similarity algorithm.
|
| TwitterCentroidCosineSimilarity<U> |
Twitter centroid cosine: executes the centroid cosine over bipartite graphs from
the reduced graph.
|
| TwitterCentroidCosineSimilarityGridSearch<U> |
Grid search generator for Twitter version of the centroid cosine similarity algorithm.
|
| TwitterMaximumCosineSimilarity<U> |
Twitter maximum cosine: executes the maximum cosine over bipartite graphs from
the reduced graph.
|
| TwitterMaximumCosineSimilarityGridSearch<U> |
Grid search generator for Twitter version of the maximum cosine similarity algorithm.
|
| TwitterRecommender<U> |
Twitter-based recommender.
|
| TwittomenderGridSearch<U> |
Grid search generator for Twittomender CB algorithm.
|
| TwittomenderRecommender<U> |
Content-based recommendation algorithm, based on a TF-IDF scheme.
|
| UndirectedEdges |
Interface for the directed edges.
|
| UndirectedGraph<V> |
Interface for undirected graphs.
|
| UndirectedJungGraph<U> |
Undirected Graph Wrapper for JUNG
|
| UndirectedMultiEdges |
Class for the undirected multi-edges.
|
| UndirectedMultiGraph<V> |
Interface for undirected graphs.
|
| UndirectedUnweightedComplementaryGraph<U> |
Undirected unweighted complementary graph
|
| UndirectedUnweightedGraph<V> |
Interface for undirected unweighted graphs.
|
| UndirectedUnweightedGraphTest |
Class that tests the fast implementation for undirected unweighted graphs.
|
| UndirectedUnweightedGraphTest |
Class that tests the fast implementation for undirected unweighted graphs.
|
| UndirectedUnweightedMultiGraph<V> |
Interface for undirected unweighted multigraphs.
|
| UndirectedUnweightedMultigraphTest |
Class for testing the fast implementation of an undirected unweighted multigraph
|
| UndirectedWeightedComplementaryGraph<U> |
Undirected weighted complementary graph.
|
| UndirectedWeightedGraph<V> |
Interface for undirected weighted graphs.
|
| UndirectedWeightedGraphTest |
Class for testing the fast implementation for undirected weighted graphs.
|
| UndirectedWeightedGraphTest |
Class for testing the fast implementation for undirected weighted graphs.
|
| UndirectedWeightedMultiGraph<V> |
Interface for undirected weighted multigraphs.
|
| UndirectedWeightedMultigraphTest | |
| Unexpectedness<U,I> |
Global version of the unexpectedness (expected profile distance).
|
| UnexpectednessConfigurator<U,F> |
Grid search for configuring the unexpectedness of the recommendations.
|
| UntrainedException |
Exception which is thrown when a pattern cannot be classified, since the
model has not been built.
|
| UnweightedEdges |
Interface for unweighted edges.
|
| UnweightedGraph<V> |
Interface for directed graphs.
|
| UnweightedMultiEdges |
Interface for unweighted edges
|
| UnweightedMultiGraph<V> |
Interface for directed graphs.
|
| UnweightedTree<U> |
Interface for managing and creating tree graphs.
|
| UnweightedTreeTest |
Class that tests the fast unweighted implementation of trees.
|
| Updateable<U,I> |
Preference data that allows updating over time
|
| UpdateableBM25<U> |
Updateable adaptation of the BM-25 Information Retrieval Algorithm for user recommendation.
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| UpdateableFactorization<U,I> |
Updateable version of a matrix factorization.
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| UpdateableFactorizer<U,I> |
UpdateableFactorizer.
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| UpdateableFeatureIndex<F> |
Updateable index for a set of features.
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| UpdateableGraphCosineSimilarity |
Updateable version of the cosine similarity.
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| UpdateableGraphSimilarity |
Updateable similarity based on a social network graph.
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| UpdateableItemIndex<I> |
Updateable index for a set of items.
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| UpdateablePreferenceData<U,I> |
Interface for updateable preference data.
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| UpdateableRecommender<U,I> |
Interface for defining recommendation algorithms which can be updated over time.
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| UpdateableSimilarity |
Generic updateable similarity for fast data.
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| UpdateableUBkNN<U> |
Updateable version of the user-based nearest-neighbors approach.
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| UpdateableUserIndex<U> |
Updateable index for a set of users.
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| UpdateConfigurator |
Interface for configuring an update mechanism.
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| UpdateMechanism |
Class for the update mechanism for the information in the corresponding lists.
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| UpdateMechanismIdentifiers |
Identifiers for the update mechanisms for the information diffusion available in the framework.
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| UpdateParameterReader |
Class for reading an update mechanism for information diffusion.
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| UpdateSelector |
Class that selects an individual update mechanism.
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| UserBasedCFGridSearch<U> |
Grid search generator for user-based kNN collaborative filtering algorithm.
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| UserDistribution<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Distribution for information pieces.
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| UserDistributionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a distribution measuring the number of information pieces each user has received.
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| UserFastRankingRecommender<U> |
Abstract class for user recommendation in social networks.
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| UserFastRankingUpdateableRecommender<U> |
Abstract class for user recommendation in social networks.
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| UserFeatDistributionConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a distribution measuring the number of times each user feature has been received.
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| UserFeatureCount<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Metric that computes the number of different (user, feature) pairs which have appeared during the simulation.
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| UserFeatureCountConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a metric that measures the number of different (user, feature) pairs.
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| UserFeatureDistribution<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Distribution for user features.
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| UserFeatureGiniComplement<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Metric that computes the complement of the Gini coefficient over the (user, feature) pairs.
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| UserFeatureGiniComplementConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Interface for the complement of the Gini coefficient over the distribution of (user, feature) pairs.
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| UserIndexGenerator |
Class for generating a content index.
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| UserMetricReranker<U> |
Global reranker strategy that reorders the candidate users according to
a user metric that we want to optimize.
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| UserMetricReranker<U> |
Abstract implementation of a reranking strategy for contact recommendation that modifies the order
of the candidate users according to some vertex metric.
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| UserMetricReranker<U> |
Individual reranker, which reorders a recommendation according to
a user metric we want to optimize.
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| UserState<U> |
Abstract representation for the users.
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| Vector |
Class that represents a vector of real values.
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| VertexLength<U> |
Class that measures the length (sum of weights of a selection of the edges concerning it) of a vertex.
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| VertexLengthGridSearch<U> |
Grid for the lenght of a node (the sum of the weights of its edges).
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| VertexMetric<U> |
Interface for user related metrics of graphs.
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| VertexMetricFunction<U> |
Functional interface for retrieving vertex metrics metrics.
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| VertexMetricGridSearch<U> |
Class for performing the grid search for a given algorithm.
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| VertexMetricIdentifiers |
Identifiers for vertex metrics.
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| VertexMetricSelector<U> |
Class that translates from a grid to the different vertex metrics.
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| VertexMetricsTest |
Tests for complementary graph metrics.
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| VertexMetricsTest |
Automated unit tests for the vertex metrics.
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| Volume<U> |
Computes the volume of the community: the sum of the degrees
of the nodes in the community.
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| VolumeGridSearch<U> |
Grid for the volume of a node.
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| VSM<U> |
Adaptation of the TF-IDF method of Information Retrieval for user recommendation
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| VSMGridSearch<U> |
Grid search generator for the vector space model (VSM) algorithm.
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| VSMSearchEngine |
Search engine using the vector space model.
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| VSMSimilarity |
Similarity based on the vector space model from Information Retrieval.
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| WattsStrogatzGenerator<U> |
Generator for random graphs using the Watts-Strogatz model.
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| WeaklyConnectedComponents<U> |
Computes communities via the Strongly Connected Components
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| WeaklyConnectedComponentsConfigurator<U extends java.io.Serializable> |
Configurator for an algorithm that computes the weakly connected components of a graph.
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| Weakness<U> |
Computes the weakness of the pairs of nodes of a graph.
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| WeaknessGridSearch<U> |
Grid for the embeddedness of a pair of users.
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| WeaknessReranker<U> |
Swap reranker for maximizing the average weakness of the graph, i.e.
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| WeakTies<U> |
Implementation of a reranker which promotes the number of weak ties (links between communities).
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| WeakTies<U> |
Computes the number of edges between communities.
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| WeakTiesGridSearch<U> |
Grid for the number of weak ties of the graph.
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| WeakTiesReranker<U> |
Reranker that promotes the number of links between different communities.
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| WeakTiesRerankerGridSearch<U> |
Grid search for a reranker that increases the number of weak ties in the network.
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| Weight<I,W> |
Class for expressing weights.
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| WeightedEdges |
Interface for weighted edges.
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| WeightedFOAFGridSearch<U> |
Grid for the weighted neighbor overlap of a pair of users.
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| WeightedFOAFLogGridSearch<U> |
Grid for the weighted neighbor overlap of a pair of users.
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| WeightedGraph<V> |
Interface for directed graphs.
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| WeightedMultiEdges |
Interface for weighted edges
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| WeightedMultiGraph<V> |
Interface for directed graphs.
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| WeightedNeighborLogOverlap<U> |
Computes the intersection between the neighborhoods of two nodes.
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| WeightedNeighborOverlap<U> |
Computes the intersection between the neighborhoods of two nodes.
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| WeightedTree<U> |
Interface for managing and creating tree graphs.
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| Weights<I,W> |
Class for expressing weights
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| WekaInstanceReader<U> |
Reads link prediction instances from Weka.
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| WekaInstanceSet<U> |
Instance set to use with Weka classifiers.
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| WekaInstanceTranslator<U> |
Class for transforming InstanceSet to WekaInstanceSet.
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| WekaMLGridSearch<U> |
Grid search generator for LambdaMART algorithm.
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| WithCreatorFilter<U extends java.io.Serializable,I extends java.io.Serializable,F> |
The only information pieces that remain are the ones which have an associated creator.
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| WithCreatorFilterConfigurator<U extends java.io.Serializable,I extends java.io.Serializable,F> |
Configures a filter which only keeps those information pieces with a creator.
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| WrapperIndividualContentIndex<C,U> |
Individual content index builder wrapping a simple one.
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| WrapperIndividualContentIndexBuilder<C,U> |
Individual content index builder wrapping a simple one.
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| WrapperIndividualForwardContentIndex<C,U> |
Individual content index builder wrapping a simple one.
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| WrongModeException |
Exception which is thrown when a index is tried to operate in the wrong mode
(if the index is configured in read mode, and the user tries to write into it,
or if the index is configured in write mode, and the user to read it).
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| ZScoreNormalizer<I> |
Z-Score normalizer.
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