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Modeling Adoptions and the Stages of the Diffusion of Innovations.

, , and . ICDM, page 420-429. IEEE Computer Society, (2014)

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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)Balancing Prediction and Recommendation Accuracy: Hierarchical Latent Factors for Preference Data., , , and . SDM, page 1035-1046. SIAM / Omnipress, (2012)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)Efficient Methods for Influence-Based Network-Oblivious Community Detection., , and . ACM TIST, 8 (2): 32:1-32:31 (2017)Who to follow and why: link prediction with explanations., , and . KDD, page 1266-1275. ACM, (2014)Characterizing Relationships through Co-clustering - A Probabilistic Approach., , , and . KDIR, page 64-73. SciTePress, (2011)Probabilistic Sequence Modeling for Recommender Systems., , , , and . KDIR, page 75-84. SciTePress, (2012)CSI: Community-Level Social Influence Analysis., , , and . ECML/PKDD (2), volume 8189 of Lecture Notes in Computer Science, page 48-63. Springer, (2013)