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A Block Mixture Model for Pattern Discovery in Preference Data.

, , and . ICDM Workshops, page 1100-1107. IEEE Computer Society, (2010)

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A Probabilistic Hierarchical Approach for Pattern Discovery in Collaborative Filtering Data (Extended Abstract)., , and . SEBD, page 239-246. (2011)Topic-aware social influence propagation models., , and . Knowl. Inf. Syst., 37 (3): 555-584 (2013)A Block Mixture Model for Pattern Discovery in Preference Data., , and . ICDM Workshops, page 1100-1107. IEEE Computer Society, (2010)Modeling item selection and relevance for accurate recommendations: a bayesian approach., , , and . RecSys, page 21-28. ACM, (2011)Balancing Prediction and Recommendation Accuracy: Hierarchical Latent Factors for Preference Data., , , and . SDM, page 1035-1046. SIAM / Omnipress, (2012)Efficient Methods for Influence-Based Network-Oblivious Community Detection., , and . ACM Trans. Intell. Syst. Technol., 8 (2): 32:1-32:31 (2017)CSI: Community-Level Social Influence Analysis., , , and . ECML/PKDD (2), volume 8189 of Lecture Notes in Computer Science, page 48-63. Springer, (2013)An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data., , and . IIR, volume 560 of CEUR Workshop Proceedings, page 23-27. CEUR-WS.org, (2010)Influence Maximization with Viral Product Design., and . SDM, page 55-63. SIAM, (2014)Who to follow and why: link prediction with explanations., , and . KDD, page 1266-1275. ACM, (2014)