Title :
MarCol: A Market-Based Recommender System
Author :
Melamed, Dan ; Shapira, Bracha ; Elovici, Yuval
Author_Institution :
Ben-Gurion Univ. of the Negev, Be´´er Sheva
Abstract :
Collaborative information-filtering systems maintain user judgments on the relevance of data items.These systems recommend relevant information to other users on the basis of similarity between user profiles or recommended items. This market-based collaborative information-filtering system employs a pricing mechanism to motivate users to provide judgments. Results show that the model increases feedback and improves recommendation quality. MarCol uses Google as the underlying search engine. It stores all user logs, including queries and judgments.
Keywords :
information filtering; pricing; query processing; search engines; Google; MarCol; collaborative information-filtering systems; market-based recommender system; pricing mechanism; search engine; Collaboration; Collaborative work; Databases; Information filtering; Information filters; Pricing; Recommender systems; Search engines; User interfaces; Web search; information filtering; performance judgment; relevance feedback;
Journal_Title :
Intelligent Systems, IEEE
DOI :
10.1109/MIS.2007.57