Department of Computer Science & Engineering, Lehigh University
19 Memorial Dr. West; Bethlehem, PA 18015 USA
Brian D. Davison
Department of Computer Science and Engineering; Lehigh University
19 Memorial Drive West; Bethlehem, PA 18015 USA
With the increasing importance of search in guiding today’s web traffic, more and more effort has been spent to create search engine spam. Since link analysis is one of the most important factors in current commercial search engines’ ranking systems, new kinds of spam aiming at links have appeared. Building link farms is one technique that can deteriorate link-based ranking algorithms. In this paper, we present algorithms for detecting these link farms automatically by first generating a seed set based on the common link set between incoming and outgoing links of Web pages and then expanding it. Links between identified pages are reweighted, providing a modified web graph to use in ranking page importance. Experimental results show that we can identify most link farm spam pages and the final ranking results are improved for almost all tested queries.
SVM HeaderParse 0.2
Proceedings of the 14th International World Wide Web Conference