Presentation	2008-09-21 Efficient Spam Post Detection by Compression-based Measure Using Suffix Trees Takashi UEMURA, Daisuke IKEDA, Hiroki ARIMURA,
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Abstract(in English)	In this paper, we propose a content-based spam detection algorithm for blog spams and bulletin board spams. For a given document set D, our algorithm constructs a probabilistic model by using suffix trees, and detects spam documents in D. Experimental results showed that our algorithm performs well for detecting word salad spams, which are believed to be difficult to detect automatically.
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Keyword(in English)	spam detection / suffix trees / probability estimation
Paper #	DE2008-37
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Conference Information
Committee	DE
Conference Date	2008/9/14(1days)
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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)	Efficient Spam Post Detection by Compression-based Measure Using Suffix Trees
Sub Title (in English)
Keyword(1)	spam detection
Keyword(2)	suffix trees
Keyword(3)	probability estimation
1st Author's Name	Takashi UEMURA
1st Author's Affiliation	Graduate School of Information Science and Technology, Hokkaido University()
2nd Author's Name	Daisuke IKEDA
2nd Author's Affiliation	Department of Informatics, Graduate School of Information Science and Electrical Engineering Kyushu University
3rd Author's Name	Hiroki ARIMURA
3rd Author's Affiliation	Graduate School of Information Science and Technology, Hokkaido University
Date	2008-09-21
Paper #	DE2008-37
Volume (vol)	vol.108
Number (no)	211
Page	pp.pp.-
#Pages	2
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