Collaborative Filtering with Personalized Skylines

— Collaborative filtering (CF) systems exploit previous ratings and similarity in user behavior to recommend the top-k objects/records which are potentially most interesting to the user assuming a single score per object. However, in various applications a record (e.g., hotel) may be rated on several attributes (value, service etc), in which case simply returning the ones with the highest overall scores fails to capture the individual attribute characteristics and to accommodate different selection criteria. In order to enhance the flexibility of CF, we propose Collaborative Filtering Skyline (CFS), a general framework that combines the advantages of CF with those of the skyline operator. CFS generates a personalized skyline for each user based on scores of other users with similar behavior. The personalized skyline includes objects that are good on certain aspects, and eliminates the ones that are not interesting on any attribute combination. Although the integration of skylines and...

• Type: Journal
• Year: 2011
• Where: TKDE
• Authors: Ilaria Bartolini, Zhenjie Zhang, Dimitris Papadias
• Keywords: Collaborative Filtering Skyline, Personalized Skyline, TKDE 2011, User