Combating web spam with trustrank

Combating web spam with trustrank (2004)

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by Zoltán Gyöngyi , Hector Garcia-molina , Jan Pedersen

Venue:	In VLDB
Citations:	220 - 2 self

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Datum	Value	Source
TITLE	Combating web spam with trustrank	INFERENCE
AUTHOR NAME	Zoltán Gyöngyi	SVM HeaderParse 0.2
AUTHOR AFFIL	Stanford University Stanford University Yahoo! Inc.; Computer Science Department Computer Science Department 701 First Avenue	SVM HeaderParse 0.2
AUTHOR ADDR	Stanford, CA 94305 Stanford, CA 94305 Sunnyvale, CA 94089	SVM HeaderParse 0.2
AUTHOR NAME	Hector Garcia-molina	SVM HeaderParse 0.2
AUTHOR AFFIL	Stanford University Stanford University Yahoo! Inc.; Computer Science Department Computer Science Department 701 First Avenue	SVM HeaderParse 0.2
AUTHOR ADDR	Stanford, CA 94305 Stanford, CA 94305 Sunnyvale, CA 94089	SVM HeaderParse 0.2
AUTHOR NAME	Jan Pedersen	SVM HeaderParse 0.2
AUTHOR AFFIL	Stanford University Stanford University Yahoo! Inc.; Computer Science Department Computer Science Department 701 First Avenue	SVM HeaderParse 0.2
AUTHOR ADDR	Stanford, CA 94305 Stanford, CA 94305 Sunnyvale, CA 94089	SVM HeaderParse 0.2
ABSTRACT	Web spam pages use various techniques to achieve higher-than-deserved rankings in a search engine’s results. While human experts can identify spam, it is too expensive to manually evaluate a large number of pages. Instead, we propose techniques to semi-automatically separate reputable, good pages from spam. We first select a small set of seed pages to be evaluated by an expert. Once we manually identify the reputable seed pages, we use the link structure of the web to discover other pages that are likely to be good. In this paper we discuss possible ways to implement the seed selection and the discovery of good pages. We present results of experiments run on the World Wide Web indexed by AltaVista and evaluate the performance of our techniques. Our results show that we can effectively filter out spam from a significant fraction of the web, based on a good seed set of less than 200 sites. 1	SVM HeaderParse 0.2
YEAR	2004	INFERENCE
VENUE	In VLDB	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	576--587	INFERENCE
CITATIONS	13 found	ParsCit 1.0