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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
UAI
2003
13 years 5 months ago
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
Collaborative filtering (CF) and contentbased filtering (CBF) have widely been used in information filtering applications, both approaches having their individual strengths and...
Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying...
SIGIR
2004
ACM
13 years 9 months ago
A nonparametric hierarchical bayesian framework for information filtering
Information filtering has made considerable progress in recent years.The predominant approaches are content-based methods and collaborative methods. Researchers have largely conc...
Kai Yu, Volker Tresp, Shipeng Yu
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...
RECSYS
2010
ACM
13 years 3 months ago
Collaborative filtering via euclidean embedding
Recommendation systems suggest items based on user preferences. Collaborative filtering is a popular approach in which recommending is based on the rating history of the system. O...
Mohammad Khoshneshin, W. Nick Street