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SIGIR
2011
ACM
12 years 9 months ago
Collaborative competitive filtering: learning recommender using context of user choice
While a user’s preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learni...
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hon...
KDD
2006
ACM
170views Data Mining» more  KDD 2006»
14 years 6 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...
ECTEL
2006
Springer
13 years 10 months ago
Towards Community-Driven Development of Educational Materials: The Edukalibre Approach
Abstract. The libre software development model has shown how combining collective intelligence can lead to revolutionary methods that underpin major software advancements. This pap...
Jesús M. González-Barahona, Vania Di...
RECSYS
2009
ACM
14 years 21 days ago
Collaborative prediction and ranking with non-random missing data
A fundamental aspect of rating-based recommender systems is the observation process, the process by which users choose the items they rate. Nearly all research on collaborative ...
Benjamin M. Marlin, Richard S. Zemel
MIR
2010
ACM
264views Multimedia» more  MIR 2010»
14 years 21 days ago
Quest for relevant tags using local interaction networks and visual content
Typical tag recommendation systems for photos shared on social networks such as Flickr, use visual content analysis, collaborative filtering or personalization strategies to prod...
Neela Sawant, Ritendra Datta, Jia Li, James Ze Wan...