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Recommender systems, which have emerged in response to the problem of information overload, provide users with recommendations of content suited to their needs. To provide proper recommendations to users, personalized recommender systems require accurate user models of characteristics, preferences and needs. In this study, we propose a collaborative(More)
This paper proposes a collaborative filtering method with user-created tags focusing on changes of web content and internet services. Collabo-rative tagging is employed as an approach in order to grasp and filter users' preferences for items. In addition, we explore several advantages of collabora-tive tagging for future searching and information sharing(More)
To get the items that a buyer wants in an Internet auction, he must search for the items through several auction sites. When the bidding starts, the buyer needs to connect to these auction sites frequently so that he can monitor the bid states and re-bid. A reserve-price auction reduces the number of connections, but this limits the user's bidding strategy.(More)