Using patterns in the behavior of the random surfer to detect webspam beneficiaries

Abstract

In order to appear in a good position on a search engine's result list it is not enough to be relevant regarding the request. Someone also have to be "popular". This notion of popularity is calculated by the search engine and is related to links made to the webpage. In order to artificially increase their popularity, webmasters sometimes use malicious techniques referred to as Webspam. It can take many forms and is in constant evolution, but Webspam usually consists of building a specific dedicated structure of spam pages around a given target page. It is really important for a search engine to address the issue of Webspam otherwise it won't be able to provide users with fair and reliable results. In this paper we propose a technique to identify webspam through the frequency language associated with random walks amongst those dedicated structures. We identify the language by calculating the frequency of appearance of k-grams on random walks launch from every node. © 2011 Springer-Verlag.