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EPIA
2009
Springer
13 years 11 months ago
Item-Based and User-Based Incremental Collaborative Filtering for Web Recommendations
Abstract. In this paper we propose an incremental item-based collaborative filtering algorithm. It works with binary ratings (sometimes also called implicit ratings), as it is typi...
Catarina Miranda, Alípio Mário Jorge
RECSYS
2009
ACM
14 years 1 months ago
Context-based splitting of item ratings in collaborative filtering
Collaborative Filtering (CF) recommendations are computed by leveraging a historical data set of users’ ratings for items. It assumes that the users’ previously recorded ratin...
Linas Baltrunas, Francesco Ricci
SIGIR
2005
ACM
14 years 28 days ago
Scalable collaborative filtering using cluster-based smoothing
Memory-based approaches for collaborative filtering identify the similarity between two users by comparing their ratings on a set of items. In the past, the memory-based approache...
Gui-Rong Xue, Chenxi Lin, Qiang Yang, Wensi Xi, Hu...
RECSYS
2009
ACM
14 years 1 months ago
TagiCoFi: tag informed collaborative filtering
Besides the rating information, an increasing number of modern recommender systems also allow the users to add personalized tags to the items. Such tagging information may provide...
Yi Zhen, Wu-Jun Li, Dit-Yan Yeung
WECWIS
2005
IEEE
137views ECommerce» more  WECWIS 2005»
14 years 28 days ago
Using Singular Value Decomposition Approximation for Collaborative Filtering
Singular Value Decomposition (SVD), together with the Expectation-Maximization (EM) procedure, can be used to find a low-dimension model that maximizes the loglikelihood of obser...
Sheng Zhang, Weihong Wang, James Ford, Fillia Make...