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KDD
2006
ACM
170views Data Mining» more  KDD 2006»
14 years 7 months ago
Classification features for attack detection in collaborative recommender systems
Collaborative recommender systems are highly vulnerable to attack. Attackers can use automated means to inject a large number of biased profiles into such a system, resulting in r...
Robin D. Burke, Bamshad Mobasher, Chad Williams, R...
IFIPTM
2009
109views Management» more  IFIPTM 2009»
13 years 5 months ago
Elimination of Subjectivity from Trust Recommendation
In many distributed applications, a party who wishes to make a transaction requires that it has a certain level of trust in the other party. It is frequently the case that the part...
Omar Hasan, Lionel Brunie, Jean-Marc Pierson, Elis...
WS
2008
ACM
13 years 7 months ago
Recommendations based on semantically enriched museum collections
This article presents the CHIP demonstrator5 for providing personalized access to digital museum collections. It consists of three main components: Art Recommender, Tour Wizard, an...
Yiwen Wang, Natalia Stash, Lora Aroyo, Peter Gorge...
ACSW
2006
13 years 9 months ago
Event sequence mining to develop profiles for computer forensic investigation purposes
Developing profiles to describe user or system behaviour is a useful technique employed in Computer Forensic investigations. Information found in data obtained by investigators ca...
Tamas Abraham
IADIS
2003
13 years 8 months ago
Dynamic Collaborative Filtering for the World Wide Web
Collaborative Filtering systems suggest items to a user because it is highly rated by some other user with similar tastes. Although these systems are achieving great success on we...
Gulden Uchyigit, Keith L. Clark