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ICDM
2007
IEEE
147views Data Mining» more  ICDM 2007»
14 years 1 months ago
Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights
Recommender systems based on collaborative filtering predict user preferences for products or services by learning past user-item relationships. A predominant approach to collabo...
Robert M. Bell, Yehuda Koren
IIR
2010
13 years 9 months ago
An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data
Recommender systems are widely used in E-Commerce for making automatic suggestions of new items that could meet the interest of a given user. Collaborative Filtering approaches co...
Nicola Barbieri, Massimo Guarascio, Ettore Ritacco
UAI
2000
13 years 8 months ago
Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach
The growth of Internet commerce has stimulated the use of collaborative filtering (CF) algorithms as recommender systems. Such systems leverage knowledge about the known preferenc...
David M. Pennock, Eric Horvitz, Steve Lawrence, C....
CHI
2009
ACM
14 years 2 months ago
Matchin: eliciting user preferences with an online game
Eliciting user preferences for large datasets and creating rankings based on these preferences has many practical applications in community-based sites. This paper gives a new met...
Severin Hacker, Luis von Ahn
WWW
2009
ACM
14 years 2 months ago
Tagommenders: connecting users to items through tags
Tagging has emerged as a powerful mechanism that enables users to find, organize, and understand online entities. Recommender systems similarly enable users to efficiently navig...
Shilad Sen, Jesse Vig, John Riedl