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» Unifying collaborative and content-based filtering
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SIGIR
2006
ACM
14 years 6 days ago
Unifying user-based and item-based collaborative filtering approaches by similarity fusion
Memory-based methods for collaborative filtering predict new ratings by averaging (weighted) ratings between, respectively, pairs of similar users or items. In practice, a large ...
Jun Wang, Arjen P. de Vries, Marcel J. T. Reinders
RECSYS
2010
ACM
13 years 6 months ago
Collaborative filtering via euclidean embedding
Recommendation systems suggest items based on user preferences. Collaborative filtering is a popular approach in which recommending is based on the rating history of the system. O...
Mohammad Khoshneshin, W. Nick Street
RECSYS
2010
ACM
13 years 6 months ago
Recommending twitter users to follow using content and collaborative filtering approaches
Recently the world of the web has become more social and more real-time. Facebook and Twitter are perhaps the exemplars of a new generation of social, real-time web services and w...
John Hannon, Mike Bennett, Barry Smyth
JCDL
2004
ACM
146views Education» more  JCDL 2004»
13 years 11 months ago
Enhancing digital libraries with TechLens+
The number of research papers available is growing at a staggering rate. Researchers need tools to help them find the papers they should read among all the papers published each y...
Roberto Torres, Sean M. McNee, Mara Abel, Joseph A...
KAIS
2011
102views more  KAIS 2011»
13 years 1 months ago
Symbolic data analysis tools for recommendation systems
Recommendation Systems have become an important tool to cope with the information overload problem by acquiring data about the user behavior. After tracing the user behavior, throu...
Byron Leite Dantas Bezerra, Francisco de Assis Ten...