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RECSYS
2009
ACM
13 years 11 months ago
Improving rating estimation in recommender systems using aggregation- and variance-based hierarchical models
Previous work on using external aggregate rating information showed that this information can be incorporated in several different types of recommender systems and improves their...
Akhmed Umyarov, Alexander Tuzhilin
AI
2009
Springer
13 years 11 months ago
Context Dependent Movie Recommendations Using a Hierarchical Bayesian Model
Abstract. We use a hierarchical Bayesian approach to model user preferences in different contexts or settings. Unlike many previous recommenders, our approach is content-based. We...
Daniel Pomerantz, Gregory Dudek
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 5 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky