Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
A Case-Based Reasoning View of Automated Collaborative Filtering
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Influences of customer preference development on the effectiveness of recommendation strategies
Electronic Commerce Research and Applications
Semantic web recommender system based personalization service for user XQuery pattern
WINE'05 Proceedings of the First international conference on Internet and Network Economics
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In Recommender systems, collaborative filtering is the most commonly used technique. Although often successful, collaborative filtering encounters the latency problem in domains where items are frequently added, as the users have to review new items before they can be recommended. In this paper a novel approach to reduce the latency problem is proposed, based on category-based filtering and user stereotypes.