Liang, Huizhi and Xu, Yue and Li, Yuefeng and Nayak, Richi and Tao, Xiaohui (2010) Connecting users and items with weighted tags for personalized item recommendations. In: HT 2010: 21st ACM Conference on Hypertext and Hypermedia, 13-16 Jun 2010, Toronto, Canada.
Tags are an important information source in Web 2.0. They can be used to describe users’ topic preferences as well as the content of items to make personalized recommendations. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. To eliminate the noise of tags, in this paper we propose to use the multiple relationships among users, items and tags to find the semantic meaning of each tag for each user individually. With the proposed approach, the relevant tags of each item and the tag preferences of each user are determined. In addition, the user and item-based collaborative filtering combined with the content filtering approach are explored. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on real world datasets collected from Amazon.com and citeULike website.
|Item Type:||Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)|
|Additional Information:||Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.|
|Uncontrolled Keywords:||cataloguing; subject headings; tags; semantics; filtering; recommender systems; personalization; Web 2.0|
|Depositing User:||epEditor USQ|
|Date Deposited:||19 May 2011 05:17|
|Last Modified:||03 Jul 2013 00:39|
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