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» Explaining collaborative filtering recommendations
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WEBDB
2010
Springer
171views Database» more  WEBDB 2010»
14 years 27 days ago
Improved Recommendations via (More) Collaboration
We consider in this paper a popular class of recommender systems that are based on Collaborative Filtering (CF for short). CF is the process of predicting customer ratings to item...
Rubi Boim, Haim Kaplan, Tova Milo, Ronitt Rubinfel...
ECIR
2010
Springer
13 years 9 months ago
Goal-Driven Collaborative Filtering - A Directional Error Based Approach
Collaborative filtering is one of the most effective techniques for making personalized content recommendation. In the literature, a common experimental setup in the modeling phase...
Tamas Jambor, Jun Wang
I3E
2008
234views Business» more  I3E 2008»
13 years 9 months ago
Development of Recommender Systems Using User Preference Tendencies: An Algorithm for Diversifying Recommendation
Abstract. Many e-commerce sites use a recommendation system to filter the specific information that a user wants out of an overload of information. Currently, the usefulness of the...
Yuki Ogawa, Hirohiko Suwa, Hitoshi Yamamoto, Isamu...
ECAI
2008
Springer
13 years 9 months ago
Probabilistic Reinforcement Rules for Item-Based Recommender Systems
The Internet is constantly growing, proposing more and more services and sources of information. Modeling personal preferences enables recommender systems to identify relevant subs...
Sylvain Castagnos, Armelle Brun, Anne Boyer
KDD
2005
ACM
163views Data Mining» more  KDD 2005»
14 years 8 months ago
Data Sparsity Issues in the Collaborative Filtering Framework
Abstract. With the amount of available information on the Web growing rapidly with each day, the need to automatically filter the information in order to ensure greater user effici...
Miha Grcar, Dunja Mladenic, Blaz Fortuna, Marko Gr...