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INTERACT
2003
15 years 7 months ago
Confidence Displays and Training in Recommender Systems
: Recommender systems help users sort through vast quantities of information. Sometimes, however, users do not know if they can trust the recommendations they receive. Adding a con...
Sean M. McNee, Shyong K. Lam, Catherine Guetzlaff,...
KDD
2006
ACM
170views Data Mining» more  KDD 2006»
16 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...
GRAPHICSINTERFACE
2000
15 years 7 months ago
Effects of Gaze on Multiparty Mediated Communication
We evaluated effects of gaze directional and other non-verbal visual cues on multiparty mediated communication. Groups of three participants (two actors, one subject) solved langu...
Roel Vertegaal, Gerrit C. van der Veer, Harro Vons
DBSOCIAL
2011
300views Database» more  DBSOCIAL 2011»
14 years 9 months ago
Boosting video popularity through recommendation systems
While search engines are the major sources of content discovery on online content providers and e-commerce sites, their capability is limited since textual descriptions cannot ful...
Renjie Zhou, Samamon Khemmarat, Lixin Gao, Huiqian...
WWW
2011
ACM
15 years 1 months ago
Ranking in context-aware recommender systems
As context is acknowledged as an important factor that can affect users’ preferences, many researchers have worked on improving the quality of recommender systems by utilizing ...
Minsuk Kahng, Sangkeun Lee, Sang-goo Lee