Class InverseEdgeMetricReranker<U>
java.lang.Object
es.uam.eps.ir.relison.links.recommendation.reranking.global.globalranking.GlobalRankingGreedyReranker<U,I>
es.uam.eps.ir.relison.links.recommendation.reranking.global.globalranking.GlobalRankingLambdaReranker<U,U>
es.uam.eps.ir.relison.links.recommendation.reranking.global.globalranking.edge.EdgeMetricReranker<U>
es.uam.eps.ir.relison.links.recommendation.reranking.global.globalranking.edge.InverseEdgeMetricReranker<U>
- Type Parameters:
U
- type of the users.
- All Implemented Interfaces:
GlobalReranker<U,U>
public class InverseEdgeMetricReranker<U> extends EdgeMetricReranker<U>
Global reranker strategy that minimizes the average value of an edge metric.
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Field Summary
Fields inherited from class es.uam.eps.ir.relison.links.recommendation.reranking.global.globalranking.edge.EdgeMetricReranker
graph, metric
Fields inherited from class es.uam.eps.ir.relison.links.recommendation.reranking.global.globalranking.GlobalRankingLambdaReranker
lambda, novStats, recStats
Fields inherited from class es.uam.eps.ir.relison.links.recommendation.reranking.global.globalranking.GlobalRankingGreedyReranker
cutOff
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Constructor Summary
Constructors Constructor Description InverseEdgeMetricReranker(double lambda, int cutoff, java.util.function.Supplier<Normalizer<U>> norm, Graph<U> graph, PairMetric<U> metric)
Constructor. -
Method Summary
Methods inherited from class es.uam.eps.ir.relison.links.recommendation.reranking.global.globalranking.edge.EdgeMetricReranker
update
Methods inherited from class es.uam.eps.ir.relison.links.recommendation.reranking.global.globalranking.GlobalRankingLambdaReranker
score, selectRecommendation
Methods inherited from class es.uam.eps.ir.relison.links.recommendation.reranking.global.globalranking.GlobalRankingGreedyReranker
rerankRecommendations
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Constructor Details
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InverseEdgeMetricReranker
public InverseEdgeMetricReranker(double lambda, int cutoff, java.util.function.Supplier<Normalizer<U>> norm, Graph<U> graph, PairMetric<U> metric)Constructor.- Parameters:
lambda
- trade-off between the recommendation score and the novelty/diversity value.cutoff
- number of elements to take.norm
- the normalization strategy.graph
- the original graph.metric
- the metric we want to optimize.
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Method Details
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nov
Description copied from class:GlobalRankingLambdaReranker
Finds the novelty score for a user-item pair.- Specified by:
nov
in classGlobalRankingLambdaReranker<U,U>
- Parameters:
user
- the target user.iv
- the candidate item (with its score).- Returns:
- the novelty value for the item.
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