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ISMIS
2005
Springer
14 years 2 months ago
Incremental Collaborative Filtering for Highly-Scalable Recommendation Algorithms
Most recommendation systems employ variations of Collaborative Filtering (CF) for formulating suggestions of items relevant to users’ interests. However, CF requires expensive co...
Manos Papagelis, Ioannis Rousidis, Dimitris Plexou...
FLAIRS
2008
13 years 11 months ago
A Mixture Imputation-Boosted Collaborative Filter
Recommendation systems suggest products to users. Collaborative filtering (CF) systems, which base those recommendations on a database of previous ratings by various users and pro...
Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greine...
ECIR
2006
Springer
13 years 10 months ago
A User-Item Relevance Model for Log-Based Collaborative Filtering
Abstract. Implicit acquisition of user preferences makes log-based collaborative filtering favorable in practice to accomplish recommendations. In this paper, we follow a formal ap...
Jun Wang, Arjen P. de Vries, Marcel J. T. Reinders
WWW
2007
ACM
14 years 10 months ago
Google news personalization: scalable online collaborative filtering
Several approaches to collaborative filtering have been studied but seldom have studies been reported for large (several million users and items) and dynamic (the underlying item ...
Abhinandan Das, Mayur Datar, Ashutosh Garg, ShyamS...
UAI
2004
13 years 10 months ago
A Bayesian Approach toward Active Learning for Collaborative Filtering
Collaborative filtering is a useful technique for exploiting the preference patterns of a group of users to predict the utility of items for the active user. In general, the perfo...
Rong Jin, Luo Si