Collaborative filtering recommender systems using tag information
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Description
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.
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| ID Code: | 29734 | ||||||
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| Item Type: | Chapter in Book, Report or Conference volume (Conference contribution) | ||||||
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| Measurements or Duration: | 4 pages | ||||||
| Keywords: | collaborative filtering, collaborative tagging, recommender systems, user profiling | ||||||
| DOI: | 10.1109/WIIAT.2008.97 | ||||||
| ISBN: | 978-0-7695-3496-1 | ||||||
| Pure ID: | 33565182 | ||||||
| Divisions: | ?? 16 ?? Past > QUT Faculties & Divisions > Faculty of Science and Technology Past > QUT Faculties & Divisions > Science & Engineering Faculty Current > Research Centres > Australian Research Centre for Aerospace Automation |
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| Copyright Owner: | Consult author(s) regarding copyright matters | ||||||
| Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||||||
| Deposited On: | 19 Jan 2010 22:25 | ||||||
| Last Modified: | 03 Mar 2024 10:11 |
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Collaborative filtering recommender systems using tag information. (deposited 12 Feb 2010 12:41)
- Collaborative filtering recommender systems using tag information. (deposited 19 Jan 2010 22:25) [Currently Displayed]
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