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RecSys 2016: Paper Session 6 - Optimizing Similar Item Recommendations
RecSys 2016: Paper Session 6 - Deep Neural Networks for YouTube Recommendations
RecSys 2016: Paper Session 1 - Contrasting Offline and Online Results when Evaluating Recommendation
Paper Session 6: Uplift-based Evaluation and Optimization of Recommenders - M Sato, et al.
RecSys 2016: Paper Session 2 - Local Item Item Models For Top-N Recommendation
RecSys 2016: Paper Session 7 - Past, Present, & Future of Recommender Systems: Industry Perspective
RecSys 2016: Paper Session 7 - Behaviorism is Not Enough: Better Recommendations
RecSys 2016: Paper Session 9 - Modelling Contextual Information in Session-Aware Recommender Systems
Next-item Recommendations in Short Sessions
PS 6: Judging similarity: a user-centric study of related item recommendations Yuan Yao
RecSys 2016: Paper Session 1 - A Scalable Approach for Periodical Personalized Recommendations
Paper Session 6: Personalized Diffusions for Top-N Recommendation - A. Nikolakopoulos et al.
