Improving recommendation based on features' co-occurrence effects in collaborative tagging systems

Hao Han; Yi Cai; Yifeng Shao; Qing Li

doi:10.1007/978-3-642-29253-8_61

Improving recommendation based on features' co-occurrence effects in collaborative tagging systems

Hao Han, Yi Cai, Yifeng Shao, Qing Li

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

7 Citations (Scopus)

Abstract

Currently, recommender system becomes more and more important and challenging, as users demand higher recommendation quality. Collaborative tagging systems allow users to annotate resources with their own tags which can reflect users' attitude on these resources and some attributes of resources. Based on our observation, we notice that there is co-occurrence effect of features, which may cause the change of user's favor on resources. Current recommendation methods do not take it into consideration. In this paper, we propose an assistant and enhanced method to improve the performance of other methods by combining co-occurrence effect of features in collaborative tagging environment.

Original language	English
Title of host publication	Web Technologies and Applications - 14th Asia-Pacific Web Conference, APWeb 2012, Proceedings
Pages	652-659
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-29253-8_61
Publication status	Published - 18 Apr 2012
Externally published	Yes
Event	14th Asia Pacific Web Technology Conference, APWeb 2012 - Kunming, China Duration: 11 Apr 2012 → 13 Apr 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7235 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th Asia Pacific Web Technology Conference, APWeb 2012
Country/Territory	China
City	Kunming
Period	11/04/12 → 13/04/12

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

More information

10.1007/978-3-642-29253-8_61

Cite this

Han, H., Cai, Y., Shao, Y., & Li, Q. (2012). Improving recommendation based on features' co-occurrence effects in collaborative tagging systems. In Web Technologies and Applications - 14th Asia-Pacific Web Conference, APWeb 2012, Proceedings (pp. 652-659). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7235 LNCS). https://doi.org/10.1007/978-3-642-29253-8_61

Han, Hao ; Cai, Yi ; Shao, Yifeng et al. / Improving recommendation based on features' co-occurrence effects in collaborative tagging systems. Web Technologies and Applications - 14th Asia-Pacific Web Conference, APWeb 2012, Proceedings. 2012. pp. 652-659 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Currently, recommender system becomes more and more important and challenging, as users demand higher recommendation quality. Collaborative tagging systems allow users to annotate resources with their own tags which can reflect users' attitude on these resources and some attributes of resources. Based on our observation, we notice that there is co-occurrence effect of features, which may cause the change of user's favor on resources. Current recommendation methods do not take it into consideration. In this paper, we propose an assistant and enhanced method to improve the performance of other methods by combining co-occurrence effect of features in collaborative tagging environment.",

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Han, H, Cai, Y, Shao, Y & Li, Q 2012, Improving recommendation based on features' co-occurrence effects in collaborative tagging systems. in Web Technologies and Applications - 14th Asia-Pacific Web Conference, APWeb 2012, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7235 LNCS, pp. 652-659, 14th Asia Pacific Web Technology Conference, APWeb 2012, Kunming, China, 11/04/12. https://doi.org/10.1007/978-3-642-29253-8_61

Improving recommendation based on features' co-occurrence effects in collaborative tagging systems. / Han, Hao; Cai, Yi; Shao, Yifeng et al.
Web Technologies and Applications - 14th Asia-Pacific Web Conference, APWeb 2012, Proceedings. 2012. p. 652-659 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7235 LNCS).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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Han H, Cai Y, Shao Y, Li Q. Improving recommendation based on features' co-occurrence effects in collaborative tagging systems. In Web Technologies and Applications - 14th Asia-Pacific Web Conference, APWeb 2012, Proceedings. 2012. p. 652-659. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-29253-8_61

Improving recommendation based on features' co-occurrence effects in collaborative tagging systems

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