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ICPR
2008
IEEE
14 years 9 months ago
Efficient user preference predictions using collaborative filtering
Two major challenges in collaborative filtering are the efficiency of the algorithms and the quality of the recommendations. A variety of machine learning methods have been applie...
C. Lee Giles, Yang Song
IAT
2009
IEEE
14 years 2 months ago
Social Trust-Aware Recommendation System: A T-Index Approach
Collaborative Filtering based on similarity suffers from a variety of problems such as sparsity and scalability. In this paper, we propose an ontological model of trust between us...
Alireza Zarghami, Soude Fazeli, Nima Dokoohaki, Mi...
DMSN
2004
ACM
14 years 1 months ago
Predictive filtering: a learning-based approach to data stream filtering
Recent years have witnessed an increasing interest in filtering of distributed data streams, such as those produced by networked sensors. The focus is to conserve bandwidth and se...
Vibhore Kumar, Brian F. Cooper, Shamkant B. Navath...
ICWSM
2009
13 years 5 months ago
A Comparative Analysis of Trust-Enhanced Recommenders for Controversial Items
A particularly challenging task for recommender systems (RSs) is deciding whether to recommend an item that received a variety of high and low scores from its users. RSs that inco...
Patricia Victor, Chris Cornelis, Martine De Cock, ...
UAI
2003
13 years 9 months ago
Preference-based Graphic Models for Collaborative Filtering
Collaborative filtering is a very useful general technique for exploiting the preference patterns of a group of users to predict the utility of items to a particular user. Previou...
Rong Jin, Luo Si, ChengXiang Zhai