Class ClusteringCoefficientComplement<U>
java.lang.Object
es.uam.eps.ir.ranksys.novdiv.reranking.PermutationReranker<U,I>
es.uam.eps.ir.ranksys.novdiv.reranking.GreedyReranker<U,I>
es.uam.eps.ir.relison.links.recommendation.reranking.local.LambdaReranker<U,U>
es.uam.eps.ir.relison.links.recommendation.reranking.local.graph.ClusteringCoefficientComplement<U>
- Type Parameters:
U
- Type of the users.
- All Implemented Interfaces:
es.uam.eps.ir.ranksys.novdiv.reranking.Reranker<U,U>
public class ClusteringCoefficientComplement<U> extends LambdaReranker<U,U>
Reranker that tries to promote the opposite of the clustering coefficient of
the graph.
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Nested Class Summary
Nested Classes Modifier and Type Class Description protected class
ClusteringCoefficientComplement.ClusteringCoefficientUserReranker
The individual reranker.Nested classes/interfaces inherited from class es.uam.eps.ir.relison.links.recommendation.reranking.local.LambdaReranker
LambdaReranker.LambdaUserReranker
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Field Summary
Fields Modifier and Type Field Description private Graph<U>
graph
The original graph.private double
triangles
The number of triangles in the graph.private double
triplets
The number of triads in the graph.Fields inherited from class es.uam.eps.ir.relison.links.recommendation.reranking.local.LambdaReranker
lambda
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Constructor Summary
Constructors Constructor Description ClusteringCoefficientComplement(double lambda, int cutoff, java.util.function.Supplier<Normalizer<U>> norm, Graph<U> graph)
Constructor. -
Method Summary
Modifier and Type Method Description protected es.uam.eps.ir.ranksys.novdiv.reranking.GreedyReranker.GreedyUserReranker<U,U>
getUserReranker(es.uam.eps.ir.ranksys.core.Recommendation<U,U> r, int i)
Methods inherited from class es.uam.eps.ir.relison.links.recommendation.reranking.local.LambdaReranker
rerankPermutation
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Field Details
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Constructor Details
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ClusteringCoefficientComplement
public ClusteringCoefficientComplement(double lambda, int cutoff, java.util.function.Supplier<Normalizer<U>> norm, Graph<U> graph)Constructor.- Parameters:
lambda
- param that establishes a balance between the score and the novelty/diversity value.cutoff
- number of elements to take.norm
- the normalization function.graph
- the graph.
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Method Details
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getUserReranker
protected es.uam.eps.ir.ranksys.novdiv.reranking.GreedyReranker.GreedyUserReranker<U,U> getUserReranker(es.uam.eps.ir.ranksys.core.Recommendation<U,U> r, int i)- Specified by:
getUserReranker
in classLambdaReranker<U,U>
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