5 records found
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GAPfm: Optimal top-n recommendations for graded relevance domains
Learning to rank for recommender systems
xCLiMF: Optimizing expected reciprocal rank for data with multiple levels of relevance
TFMAP: Optimizing MAP for top-n context-aware recommendation
CLiMF: learning to maximize reciprocal rank with collaborative less-is-more filtering
