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AH
2008
Springer
13 years 11 months ago
Locally Adaptive Neighborhood Selection for Collaborative Filtering Recommendations
Abstract. User-to-user similarity is a fundamental component of Collaborative Filtering (CF) recommender systems. In user-to-user similarity the ratings assigned by two users to a ...
Linas Baltrunas, Francesco Ricci
AMM
2011
118views more  AMM 2011»
13 years 9 days ago
From Community Detection to Mentor Selection in Rating-Free Collaborative Filtering
—The number of resources or items that users can now access when navigating on the Web or using e-services, is so huge that these might feel lost due to the presence of too much ...
Armelle Brun, Sylvain Castagnos, Anne Boyer
RECSYS
2009
ACM
13 years 11 months ago
Rating aggregation in collaborative filtering systems
Recommender systems based on user feedback rank items by aggregating users’ ratings in order to select those that are ranked highest. Ratings are usually aggregated using a weig...
Florent Garcin, Boi Faltings, Radu Jurca, Nadine J...
SIGIR
2006
ACM
13 years 11 months 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
ISMIS
2009
Springer
13 years 11 months ago
Alternative Formulas for Rating Prediction Using Collaborative Filtering
This paper proposes and evaluates several alternate design choices for common prediction metrics employed by neighborhood-based collaborative filtering approach. It first explores ...
Amar Saric, Mirsad Hadzikadic, David Wilson