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» Finding group shilling in recommendation system
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WWW
2005
ACM
14 years 12 months ago
Finding group shilling in recommendation system
In the age of information explosion, recommendation system has been proved effective to cope with information overload in ecommerce area. However, unscrupulous producers shill the...
Xue-Feng Su, Hua-Jun Zeng, Zheng Chen
WWW
2004
ACM
14 years 12 months ago
Shilling recommender systems for fun and profit
Recommender systems have emerged in the past several years as an effective way to help people cope with the problem of information overload. One application in which they have bec...
Shyong K. Lam, John Riedl
KDD
2006
ACM
172views Data Mining» more  KDD 2006»
14 years 11 months ago
Attack detection in time series for recommender systems
Recent research has identified significant vulnerabilities in recommender systems. Shilling attacks, in which attackers introduce biased ratings in order to influence future recom...
Sheng Zhang, Amit Chakrabarti, James Ford, Fillia ...
KBS
2006
127views more  KBS 2006»
13 years 11 months ago
Collaborative Recommending using Formal Concept Analysis
We show how Formal Concept Analysis (FCA) can be applied to Collaborative Recommenders. FCA is a mathematical method for analysing binary relations. Here we apply it to the relati...
Patrick du Boucher-Ryan, Derek G. Bridge
HICSS
2007
IEEE
114views Biometrics» more  HICSS 2007»
14 years 5 months ago
Consumers' Interest in Personalized Recommendations: The Role of Product-Involvement and Opinion Seeking
The best recommender system is useless if consumers are not interested in its recommendations. Hence it is vital for e-commerce operators who apply recommender systems to get insi...
Nicolas Knotzer, Maria Madlberger