Personalized tag recommendation based on user preference and content

Authors:
Zhaoxin Shu;Li Yu;Xiaoping Yang
Affiliations:
School of Information, Renmin University of China, Beijing, P.R. China;School of Information, Renmin University of China, Beijing, P.R. China;School of Information, Renmin University of China, Beijing, P.R. China
Venue:
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Year:
2010

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Abstract

With the widely use of collaborative tagging system nowadays, users could tag their favorite resources with free keywords. Tag recommendation technology is developed to help users in the process of tagging. However, most of the tag recommendation methods are merely based on the content of tagged resource. In this paper, it is argued that tags depend not only on the content of resource, but also on user preference. As such, a hybrid personalized tag recommendation method based on user preference and content is proposed. The experiment results show that the proposed method has advantages over traditional content-based methods.