Connecting users and items with weighted tags for personalized item recommendations
Paper
Paper/Presentation Title | Connecting users and items with weighted tags for personalized item recommendations |
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Presentation Type | Paper |
Authors | Liang, Huizhi (Author), Xu, Yue (Author), Li, Yuefeng (Author), Nayak, Richi (Author) and Tao, Xiaohui (Author) |
Editors | Chignell, Mark and Toms, Elaine |
Journal or Proceedings Title | Proceedings of the 21st ACM Conference on Hypertext and Hypermedia (HT 2010) |
Number of Pages | 10 |
Year | 2010 |
Place of Publication | New York, USA |
ISBN | 9781450300414 |
Digital Object Identifier (DOI) | https://doi.org/10.1145/1810617.1810628 |
Web Address (URL) of Paper | http://portal.acm.org/citation.cfm?id=1810628 |
Conference/Event | HT 2010: 21st ACM Conference on Hypertext and Hypermedia |
Event Details | HT 2010: 21st ACM Conference on Hypertext and Hypermedia Event Date 13 to end of 16 Jun 2010 Event Location Toronto, Canada |
Abstract | 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. |
Keywords | cataloguing; subject headings; tags; semantics; filtering; recommender systems; personalization; Web 2.0 |
ANZSRC Field of Research 2020 | 461301. Coding, information theory and compression |
460612. Service oriented computing | |
460508. Information retrieval and web search | |
Public Notes | 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. |
Byline Affiliations | Queensland University of Technology |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q0v2z/connecting-users-and-items-with-weighted-tags-for-personalized-item-recommendations
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