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CIKM
2008
Springer

Predicting web spam with HTTP session information

8 years 10 months ago
Predicting web spam with HTTP session information
Web spam is a widely-recognized threat to the quality and security of the Web. Web spam pages pollute search engine indexes, burden Web crawlers and Web mining services, and expose users to dangerous Web-borne malware. To defend against Web spam, most previous research analyzes the contents of Web pages and the link structure of the Web graph. Unfortunately, these heavyweight approaches require full downloads of both legitimate and spam pages to be effective, making real-time deployment of these techniques infeasible for Web browsers, high-performance Web crawlers, and real-time Web applications. In this paper, we present a lightweight, predictive approach to Web spam classification that relies exclusively on HTTP session information (i.e., hosting IP addresses and HTTP session headers). Concretely, we built an HTTP session classifier based on our predictive technique, and by incorporating this classifier into HTTP retrieval operations, we are able to detect Web spam pages before the ...
Steve Webb, James Caverlee, Calton Pu
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where CIKM
Authors Steve Webb, James Caverlee, Calton Pu
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