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» Using mixture models for collaborative filtering
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IR
2006
13 years 3 months ago
A study of mixture models for collaborative filtering
Collaborative filtering is a general technique for exploiting the preference patterns of a group of users to predict the utility of items for a particular user. Three different co...
Rong Jin, Luo Si, Chengxiang Zhai
STOC
2004
ACM
145views Algorithms» more  STOC 2004»
14 years 3 months ago
Using mixture models for collaborative filtering
A collaborative filtering system at an e-commerce site or similar service uses data about aggregate user behavior to make recommendations tailored to specific user interests. We d...
Jon M. Kleinberg, Mark Sandler
WEBI
2007
Springer
13 years 9 months ago
Hybrid Collaborative Filtering Algorithms Using a Mixture of Experts
Collaborative filtering (CF) is one of the most successful approaches for recommendation. In this paper, we propose two hybrid CF algorithms, sequential mixture CF and joint mixtu...
Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaa...
CIKM
2004
Springer
13 years 9 months ago
Unified filtering by combining collaborative filtering and content-based filtering via mixture model and exponential model
Collaborative filtering and content-based filtering are two types of information filtering techniques. Combining these two techniques can improve the recommendation effectiveness....
Luo Si, Rong Jin
AAAI
2010
13 years 5 months ago
Bayesian Matrix Factorization with Side Information and Dirichlet Process Mixtures
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
Ian Porteous, Arthur Asuncion, Max Welling