Web spam identification through content and hyperlinks

We present an algorithm, witch, that learns to detect spam hosts or pages on the Web. Unlike most other approaches, it simultaneously exploits the structure of the Web graph as well as page contents and features. The method is efficient, scalable, and provides state-of-the-art accuracy on a standard Web spam benchmark. Categories and Subject Descriptors H.4.m [Information Systems Applications]: Miscellaneous; I.2.6 [Learning]; I.5 [Pattern Recognition] Keywords Web spam, graph regularization, Support Vector Machines

• Type: Conference
• Year: 2008
• Where: AIRWEB
• Authors: Jacob Abernethy, Olivier Chapelle, Carlos Castillo
• Keywords: AIRWEB 2008, Internet Technology, Keywords Web Spam, Web Spam, Web Spam Benchmark