Collaborative filtering recommender systems using tag information
Contribuinte(s) |
Li, Y Pasi, G Zhang, C Cercone, N Cao, L |
---|---|
Data(s) |
2008
|
Resumo |
Recommender Systems is one of the effective tools to deal with information overload issue. Similar with the explicit rating and other implicit rating behaviours such as purchase behaviour, click streams, and browsing history etc., the tagging information implies user’s important personal interests and preferences information, which can be used to recommend personalized items to users. This paper is to explore how to utilize tagging information to do personalized recommendations. Based on the distinctive three dimensional relationships among users, tags and items, a new user profiling and similarity measure method is proposed. The experiments suggest that the proposed approach is better than the traditional collaborative filtering recommender systems using only rating data. |
Formato |
application/pdf |
Identificador | |
Publicador |
IEEE Computer Society |
Relação |
http://eprints.qut.edu.au/29734/2/29734.pdf DOI:10.1109/WIIAT.2008.97 Liang, Huizhi, Xu, Yue, Li, Yuefeng, & Nayak, Richi (2008) Collaborative filtering recommender systems using tag information. In Li, Y, Pasi, G, Zhang, C, Cercone, N, & Cao, L (Eds.) Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence, IEEE Computer Society, Australia, New South Wales, Sydney, pp. 59-62. |
Direitos |
Copyright 2008 IEEE |
Fonte |
Faculty of Science and Technology; School of Information Technology; School of Information Systems |
Palavras-Chave | #080704 Information Retrieval and Web Search #collaborative filtering, collaborative tagging, recommender systems, user profiling |
Tipo |
Conference Paper |