Presentation	2008/11/24 Spammer Detection based on Tagging Behavior in Social Bookmarking Systems Yoshihiko SUHARA, Yukio UEMATSU, Takafumi INOUE, Ryoji KATAOKA,
PDF Download Page	PDF download Page Link
Abstract(in Japanese)	(See Japanese page)
Abstract(in English)	In this paper, we consider that spammers in social bookmarking systems have different tagging behavior from non-spammer. We propose the method that classify the spammers using the classifier generated by supervised learning from the feature based on users' tagging behavior. Evaluation results showed that proposed method could reduce the misclassification of non-spammer users while keep the spammer classification accuracy compared with the conventional methods.
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)	social annotation / spammer detection
Paper #	DE2008-54
Date of Issue

Conference Information
Committee	DE
Conference Date	2008/11/24(1days)
Place (in Japanese)	(See Japanese page)
Place (in English)
Topics (in Japanese)	(See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To	Data Engineering (DE)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Spammer Detection based on Tagging Behavior in Social Bookmarking Systems
Sub Title (in English)
Keyword(1)	social annotation
Keyword(2)	spammer detection
1st Author's Name	Yoshihiko SUHARA
1st Author's Affiliation	NTT Cyber Solutions Laboratories, NTT Corporation()
2nd Author's Name	Yukio UEMATSU
2nd Author's Affiliation	NTT Cyber Solutions Laboratories, NTT Corporation
3rd Author's Name	Takafumi INOUE
3rd Author's Affiliation	NTT Cyber Solutions Laboratories, NTT Corporation
4th Author's Name	Ryoji KATAOKA
4th Author's Affiliation	NTT Cyber Solutions Laboratories, NTT Corporation
Date	2008/11/24
Paper #	DE2008-54
Volume (vol)	vol.108
Number (no)	329
Page	pp.pp.-
#Pages	2
Date of Issue