U - type of the usersI - type of the itemspublic class AggregateDiversityMetric<U,I> extends EIURD<U,I>
EIURD
multiplied by the cut-off.
S. Vargas. Novelty and diversity evaluation and enhancement in Recommender
Systems. PhD Thesis.
G. Adomavicius and Y. Kwon. Improving aggregate recommendation diversity
using rank-based techniques. TKDE vol. 24 no. 5, 2012.cutoff, freeNorm, itemCount, itemWeight, numUsers| Constructor and Description |
|---|
AggregateDiversityMetric(int cutoff,
RelevanceModel<U,I> relModel)
Constructor.
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| Modifier and Type | Method and Description |
|---|---|
double |
evaluate()
Evaluates the metric for the recommendations added so far.
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add, combine, resetpublic AggregateDiversityMetric(int cutoff,
RelevanceModel<U,I> relModel)
cutoff - maximum length of the recommendation lists that is evaluatedrelModel - relevance modelpublic double evaluate()
evaluate in interface SystemMetric<U,I>evaluate in class AbstractSalesDiversityMetric<U,I>Copyright © 2016. All rights reserved.