Personalized recommender systems integrating tags and item taxonomy

Liang, Huizhi, Xu, Yue, & Li, Yuefeng (2012) Personalized recommender systems integrating tags and item taxonomy. Web Intelligence and Agent Systems, 10(3), pp. 277-289.

View at publisher (open access)


The social tags in Web 2.0 are becoming another important information source to profile users' interests and preferences to make personalized recommendations. To solve the problem of low information sharing caused by the free-style vocabulary of tags and the long tails of the distribution of tags and items, this paper proposes an approach to integrate the social tags given by users and the item taxonomy with standard vocabulary and hierarchical structure provided by experts to make personalized recommendations. The experimental results show that the proposed approach can effectively improve the information sharing and recommendation accuracy.

Impact and interest:

0 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

157 since deposited on 07 Mar 2013
9 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 57837
Item Type: Journal Article
Refereed: Yes
Keywords: Recommender systems, tags, user profiling, personalization, Taxonomy
DOI: 10.3233/WIA-2012-0246
ISSN: 1570-1263
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 IOS Press & Authors
Copyright Statement: All rights reserved
Deposited On: 07 Mar 2013 02:48
Last Modified: 10 Mar 2013 04:36

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page