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ECAI
2008
Springer
11 years 11 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
STAIRS
2008
169views Education» more  STAIRS 2008»
11 years 11 months ago
Probabilistic Association Rules for Item-Based Recommender Systems
Since the beginning of the 1990's, the Internet has constantly grown, proposing more and more services and sources of information. The challenge is no longer to provide users ...
Sylvain Castagnos, Armelle Brun, Anne Boyer
AIRS
2005
Springer
12 years 3 months ago
A Probabilistic Model for Music Recommendation Considering Audio Features
In order to make personalized recommendations, many collaborative music recommender systems (CMRS) focused on capturing precise similarities among users or items based on user hist...
Qing Li, Sung-Hyon Myaeng, Donghai Guan, Byeong Ma...
IPM
2007
182views more  IPM 2007»
11 years 9 months ago
A probabilistic music recommender considering user opinions and audio features
A recommender system has an obvious appeal in an environment where the amount of on-line information vastly outstrips any individual’s capability to survey. Music recommendation...
Qing Li, Sung-Hyon Myaeng, Byeong Man Kim
DEBU
2008
186views more  DEBU 2008»
11 years 9 months ago
A Survey of Collaborative Recommendation and the Robustness of Model-Based Algorithms
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-...
Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke
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