WWW2009 EPrints

Combining Anchor Text Categorization and Graph Analysis for Paid Link Detection

This item is a Poster.

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In order to artificially boost the rank of commercial pages in search engine results, search engine optimizers pay for links to these pages on other websites. Identifying paid links is important for a web search engine to produce highly relevant results. In this paper we introduce a novel method of identifying such links. We start with training a classifier of anchor text topics and analyzing web pages for diversity of their outgoing commercial links. Then we use this information and analyze link graph of the Russian Web to find pages that sell links and sites that buy links and to identify the paid links. Testing on manually marked samples showed high efficiency of the algorithm.

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About this site

This website has been set up for WWW2009 by Christopher Gutteridge of the University of Southampton, using our EPrints software.


We (Southampton EPrints Project) intend to preserve the files and HTML pages of this site for many years, however we will turn it into flat files for long term preservation. This means that at some point in the months after the conference the search, metadata-export, JSON interface, OAI etc. will be disabled as we "fossilize" the site. Please plan accordingly. Feel free to ask nicely for us to keep the dynamic site online longer if there's a rally good (or cool) use for it... [this has now happened, this site is now static]