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SAC
2008
ACM
13 years 4 months ago
Tag-aware recommender systems by fusion of collaborative filtering algorithms
Recommender Systems (RS) aim at predicting items or ratings of items that the user are interested in. Collaborative Filtering (CF) algorithms such as user- and item-based methods ...
Karen H. L. Tso-Sutter, Leandro Balby Marinho, Lar...
DEBU
2008
165views more  DEBU 2008»
13 years 4 months ago
A Survey of Attack-Resistant Collaborative Filtering Algorithms
With the increasing popularity of recommender systems in commercial services, the quality of recommendations has increasingly become an important to study, much like the quality o...
Bhaskar Mehta, Thomas Hofmann
RECSYS
2010
ACM
13 years 4 months ago
Group recommendations with rank aggregation and collaborative filtering
The majority of recommender systems are designed to make recommendations for individual users. However, in some circumstances the items to be selected are not intended for persona...
Linas Baltrunas, Tadas Makcinskas, Francesco Ricci
AAAI
2006
13 years 6 months ago
Model-Based Collaborative Filtering as a Defense against Profile Injection Attacks
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
Bamshad Mobasher, Robin D. Burke, Jeff J. Sandvig
SIGIR
2006
ACM
13 years 10 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