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KDD
2007
ACM
191views Data Mining» more  KDD 2007»
16 years 7 days ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
CORR
2010
Springer
169views Education» more  CORR 2010»
14 years 6 months ago
Recommender Systems by means of Information Retrieval
In this paper we present a method for reformulating the Recommender Systems problem in an Information Retrieval one. In our tests we have a dataset of users who give ratings for s...
Alberto Costa, Fabio Roda
RECSYS
2009
ACM
15 years 6 months ago
Using a trust network to improve top-N recommendation
Top-N item recommendation is one of the important tasks of recommenders. Collaborative filtering is the most popular approach to building recommender systems which can predict ra...
Mohsen Jamali, Martin Ester
CORR
2006
Springer
105views Education» more  CORR 2006»
14 years 12 months ago
Employing Trusted Computing for the forward pricing of pseudonyms in reputation systems
Reputation and recommendation systems are fundamental for the formation of community market places. Yet, they are easy targets for attacks which disturb a market's equilibriu...
Nicolai Kuntze, Dominique Maehler, Andreas U. Schm...
AVI
2004
15 years 1 months ago
More than the sum of its members: challenges for group recommender systems
Systems that recommend items to a group of two or more users raise a number of challenging issues that are so far only partly understood. This paper identifies four of these issue...
Anthony Jameson