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» Explaining collaborative filtering recommendations
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KDD
2009
ACM
162views Data Mining» more  KDD 2009»
14 years 8 months ago
TrustWalker: a random walk model for combining trust-based and item-based recommendation
Collaborative filtering is the most popular approach to build recommender systems and has been successfully employed in many applications. However, it cannot make recommendations ...
Mohsen Jamali, Martin Ester
ESWA
2008
152views more  ESWA 2008»
13 years 8 months ago
Collaborative recommender systems: Combining effectiveness and efficiency
Recommender systems base their operation on past user ratings over a collection of items, for instance, books, CDs, etc. Collaborative filtering (CF) is a successful recommendatio...
Panagiotis Symeonidis, Alexandros Nanopoulos, Apos...
AAAI
2006
13 years 9 months ago
Bookmark Hierarchies and Collaborative Recommendation
GiveALink.org is a social bookmarking site where users may donate and view their personal bookmark files online securely. The bookmarks are analyzed to build a new generation of i...
Benjamin Markines, Lubomira Stoilova, Filippo Menc...
ICML
1998
IEEE
14 years 8 months ago
Learning Collaborative Information Filters
Predicting items a user would like on the basis of other users' ratings for these items has become a well-established strategy adopted by many recommendation services on the ...
Daniel Billsus, Michael J. Pazzani
STAIRS
2008
169views Education» more  STAIRS 2008»
13 years 9 months ago
Probabilistic Association Rules for Item-Based Recommender Systems
Since the beginning of the 1990's, the Internet has constantly grown, proposing more and more services and sources of information. The challenge is no longer to provide users ...
Sylvain Castagnos, Armelle Brun, Anne Boyer