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RECSYS
2010
ACM
13 years 6 months ago
Group recommendations with rank aggregation and collaborative filtering
The majority of recommender systems are designed to make recommendations for individual users. However, in some circumstances the items to be selected are not intended for persona...
Linas Baltrunas, Tadas Makcinskas, Francesco Ricci
RECSYS
2010
ACM
13 years 6 months ago
Nantonac collaborative filtering: a model-based approach
A recommender system has to collect users' preference data. To collect such data, rating or scoring methods that use rating scales, such as good-fair-poor or a five-point-sca...
Toshihiro Kamishima, Shotaro Akaho
RECSYS
2010
ACM
13 years 4 months ago
Merging multiple criteria to identify suspicious reviews
Assessing the trustworthiness of reviews is a key issue for the maintainers of opinion sites such as TripAdvisor, given the rewards that can be derived from posting false or biase...
Guangyu Wu, Derek Greene, Padraig Cunningham
RECSYS
2010
ACM
13 years 6 months ago
Beyond accuracy: evaluating recommender systems by coverage and serendipity
When we evaluate the quality of recommender systems (RS), most approaches only focus on the predictive accuracy of these systems. Recent works suggest that beyond accuracy there i...
Mouzhi Ge, Carla Delgado-Battenfeld, Dietmar Janna...
RECSYS
2010
ACM
13 years 6 months ago
Interactive recommendations in social endorsement networks
An increasing number of social networking platforms are giving users the option to endorse entities that they find appealing, such as videos, photos, or even other users. We defin...
Theodoros Lappas, Dimitrios Gunopulos