Reasonable tag-based collaborative filtering for social tagging systems

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Reasonable tag-based collaborative filtering for social tagging systems

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Conference on Information and Knowledge Management archive
Proceeding of the 2nd ACM workshop on Information credibility on the web table of contents

Napa Valley, California, USA

SESSION: Analyzing social networks and discussion forums table of contents

Pages 11-18

Year of Publication: 2008

ISBN:978-1-60558-259-7

Authors

Reyn Y. Nakamoto	kizasi Company, Inc., Tokyo, Japan
Shinsuke Nakajima	Kyoto Sangyo University, Kyoto, Japan
Jun Miyazaki	Nara Institute of Science and Technology, Nara, Japan
Shunsuke Uemura	Nara Sangyo University, Nara, Japan
Hirokazu Kato	Nara Institute of Science and Technology, Nara, Japan
Yoichi Inagaki	kizasi Company, Inc., Tokyo, Japan

Sponsors

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 48, Downloads (12 Months): 213, Citation Count: 2

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ABSTRACT

In this paper, we present a tag-based collaborative filtering recommendation method for use with recently popular online social tagging systems. Combining the information provided by tagging systems with the effective recommendation abilities given by collaborative filtering, we provide a website recommendation system which provides relevant, credible recommendations that match the user's changing interests as well as the user's bookmarking profile. Based upon user testing, our system provides a higher level of relevant recommendations over other commonly used search and recommendation methods. We describe this system as well as the relevant user testing results and its implication towards use in online social tagging systems.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Amazon.com.http://www.amazon.com/.
	2	Citeulike.http://www.citeulike.org/.
	3	del.icio.us.http://del.icio.us/.
	4	Flickr.http://www.flickr.com/.
	5	movielens.http://www.movielens.umn.edu/.
	6	S. Golder and B. Huberman. The structure of collaborative tagging systems.
	7	R. Nakamoto, S. Nakajima, J. Miyazaki, and H. K. S. Uemura. Evaluation of tag-based contextual collaborative filtering effectiveness in website recommendation. Technical Report 131, IEICE, 2007.
	8	R. Nakamoto, S. Nakajima, J. Miyazaki, and S. Uemura. Tag-based contextual collaborative filtering. In 18th IEICE Data Engineering Workshop 2007.
	9	Paul Resnick , Neophytos Iacovou , Mitesh Suchak , Peter Bergstrom , John Riedl, GroupLens: an open architecture for collaborative filtering of netnews, Proceedings of the 1994 ACM conference on Computer supported cooperative work, p.175-186, October 22-26, 1994, Chapel Hill, North Carolina, United States [doi>10.1145/192844.192905]
	10	Xian Wu , Lei Zhang , Yong Yu, Exploring social annotations for the semantic web, Proceedings of the 15th international conference on World Wide Web, May 23-26, 2006, Edinburgh, Scotland [doi>10.1145/1135777.1135839]

CITED BY 2

	Daisuke Kitayama , Ryong Lee , Kazutoshi Sumiya, A method of analyzing credibility based on LOD control of digital maps, Proceedings of the 3rd workshop on Information credibility on the web, April 20-20, 2009, Madrid, Spain
	Daisuke Kitayama , Ryong Lee , Kazutoshi Sumiya, A credibility analyzing method of geographical objects from digital maps, Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication, January 15-16, 2009, Suwon, Korea