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Locally Adaptive Neighborhood Selection for Collaborative Filtering Recommendations., and . AH, volume 5149 of Lecture Notes in Computer Science, page 22-31. Springer, (2008)CLiMF: learning to maximize reciprocal rank with collaborative less-is-more filtering., , , , , and . RecSys, page 139-146. ACM, (2012)Frappe: Understanding the Usage and Perception of Mobile App Recommendations In-The-Wild., , , and . CoRR, (2015)Group recommendations with rank aggregation and collaborative filtering., , and . RecSys, page 119-126. ACM, (2010)Multi-dimensional Histograms with Tight Bounds for the Error., , and . IDEAS, page 105-112. IEEE Computer Society, (2006)GAPfm: optimal top-n recommendations for graded relevance domains., , , , and . CIKM, page 2261-2266. ACM, (2013)Item Weighting Techniques for Collaborative Filtering., and . Knowledge Discovery Enhanced with Semantic and Social Information, volume 220 of Studies in Computational Intelligence, (2009)Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering., , , and . RecSys, page 79-86. ACM, (2010)Exploiting contextual information in recommender systems.. RecSys, page 295-298. ACM, (2008)Deep Learning for Recommender Systems: A Netflix Case Study., , , , , and . AI Mag., 42 (3): 7-18 (2021)