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» Market-Based Recommender Systems: Learning Users' Interests ...
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AOIS
2004
13 years 6 months ago
Market-Based Recommender Systems: Learning Users' Interests by Quality Classification
Recommender systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed. However, no one technique i...
Yan Zheng Wei, Luc Moreau, Nicholas R. Jennings
IDEAL
2004
Springer
13 years 10 months ago
Learning Users' Interests in a Market-Based Recommender System
Recommender systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed. However, no one technique i...
Yan Zheng Wei, Luc Moreau, Nicholas R. Jennings
VLDB
2004
ACM
155views Database» more  VLDB 2004»
13 years 10 months ago
AWESOME - A Data Warehouse-based System for Adaptive Website Recommendations
Recommendations are crucial for the success of large websites. While there are many ways to determine recommendations, the relative quality of these recommenders depends on many f...
Andreas Thor, Erhard Rahm
SIGKDD
2008
138views more  SIGKDD 2008»
13 years 4 months ago
Learning preferences of new users in recommender systems: an information theoretic approach
Recommender systems are a nice tool to help nd items of interest from an overwhelming number of available items. Collaborative Filtering (CF), the best known technology for recomme...
Al Mamunur Rashid, George Karypis, John Riedl
IUI
2010
ACM
14 years 1 months ago
Personalized news recommendation based on click behavior
Online news reading has become very popular as the web provides access to news articles from millions of sources around the world. A key challenge of news websites is to help user...
Jiahui Liu, Peter Dolan, Elin Rønby Pederse...