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RECSYS
2009
ACM
15 years 4 months ago
Using a trust network to improve top-N recommendation
Top-N item recommendation is one of the important tasks of recommenders. Collaborative filtering is the most popular approach to building recommender systems which can predict ra...
Mohsen Jamali, Martin Ester
RECSYS
2009
ACM
15 years 4 months ago
Preference elicitation with subjective features
Utility or preference elicitation is a critical component in many recommender and decision support systems. However, most frameworks for elicitation assume a predefined set of fe...
Craig Boutilier, Kevin Regan, Paolo Viappiani
RECSYS
2009
ACM
15 years 2 months ago
Acceptance issues of personality-based recommender systems
To understand users’ acceptance of the emerging trend of personality-based recommenders (PBR), we evaluated an existing PBR using the technology acceptance model (TAM). We also ...
Rong Hu, Pearl Pu
RECSYS
2009
ACM
15 years 4 months 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
RECSYS
2009
ACM
15 years 4 months ago
TagiCoFi: tag informed collaborative filtering
Besides the rating information, an increasing number of modern recommender systems also allow the users to add personalized tags to the items. Such tagging information may provide...
Yi Zhen, Wu-Jun Li, Dit-Yan Yeung