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Selecting relevant instances for efficient and accurate collaborative filtering
2001
Proceedings of the tenth international conference on Information and knowledge management - CIKM'01
Collaborative filtering uses a database about consumers' preferences to make personal product recommendations and is achieving widespread success in both E-Commerce and Information Filtering Applications nowadays. However, the traditional collaborative filtering algorithms do not scale well to the ever-growing number of consumers. The quality of the recommendation also needs to be improved in order to gain more trust from the consumers. In this paper, we present a novel method to improve the
doi:10.1145/502585.502626
dblp:conf/cikm/YuXEK01
fatcat:uyjubupwc5aehok2dhaelf4rfm