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» Rating Elicitation Strategies for Collaborative Filtering
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ECWEB
2011
Springer
233views ECommerce» more  ECWEB 2011»
9 years 11 months ago
Rating Elicitation Strategies for Collaborative Filtering
The accuracy of collaborative ļ¬ltering recommender systems largely depends on two factors: the quality of the recommendation algorithm and the nature of the available item rating...
Mehdi Elahi, Valdemaras Repsys, Francesco Ricci
SIGIR
2004
ACM
11 years 5 months ago
A study of methods for normalizing user ratings in collaborative filtering
The goal of collaborative filtering is to make recommendations for a test user by utilizing the rating information of users who share interests similar to the test user. Because r...
Rong Jin, Luo Si
ICML
1998
IEEE
12 years 17 days 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
COOPIS
2004
IEEE
11 years 3 months ago
Trust-Aware Collaborative Filtering for Recommender Systems
Recommender Systems allow people to find the resources they need by making use of the experiences and opinions of their nearest neighbours. Costly annotations by experts are replac...
Paolo Massa, Paolo Avesani
SIGIR
2008
ACM
10 years 11 months ago
Personalized active learning for collaborative filtering
Collaborative Filtering (CF) requires user-rated training examples for statistical inference about the preferences of new users. Active learning strategies identify the most infor...
Abhay Harpale, Yiming Yang
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