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ICDM
2005
IEEE
126views Data Mining» more  ICDM 2005»
14 years 1 months ago
Segment-Based Injection Attacks against Collaborative Filtering Recommender Systems
Significant vulnerabilities have recently been identified in collaborative filtering recommender systems. Researchers have shown that attackers can manipulate a system’s reco...
Robin D. Burke, Bamshad Mobasher, Runa Bhaumik, Ch...
ICMCS
2000
IEEE
145views Multimedia» more  ICMCS 2000»
14 years 10 days ago
Temperament-Based Information Filtering: A Human Factors Approach to Information Recommendation
This paper provides an intelligent multiagent approach to incorporate human temperaments into the filtering process of an information recommendation service. Our approach is to de...
Cha-Hwa Lin, Dennis McLeod
RECSYS
2010
ACM
13 years 8 months ago
Nantonac collaborative filtering: a model-based approach
A recommender system has to collect users' preference data. To collect such data, rating or scoring methods that use rating scales, such as good-fair-poor or a five-point-sca...
Toshihiro Kamishima, Shotaro Akaho
CW
2003
IEEE
14 years 1 months ago
Development of a recommendation system with multiple subjective evaluation process models
Current BtoC recommendation services utilize consumers’ purchased log as criteria for selecting information, yet it includes little information of the reason why he bought the i...
Emi Yano, Emi Sueyoshi, Isao Shinohara, Toshikazu ...
UM
2009
Springer
14 years 14 days ago
History Dependent Recommender Systems Based on Partial Matching
Abstract. This paper focuses on the utilization of the history of navigation within recommender systems. It aims at designing a collaborative recommender based on Markov models rel...
Armelle Brun, Geoffray Bonnin, Anne Boyer