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KDD
2006
ACM
170views Data Mining» more  KDD 2006»
15 years 9 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...
88
Voted
IFIPTM
2009
109views Management» more  IFIPTM 2009»
14 years 7 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
14 years 9 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
14 years 10 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
14 years 10 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