Abstract
Most of the existing combating web spam techniques focus on the spam detection itself, which are separated from the ranking process. In this paper, we propose a two-stage ranking strategy, which makes good use of hyperlink information among Websites and Website’s intra structure information.The proposed method incorporates web spam detection into the ranking process and penalizes the ranking score of potential spam pages, instead of removing them arbitrarily. Preliminary experimental results show that our method is feasible and effective.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Benczúr, A.A., et al.: Spamrank: Fully Automatic Link Spam Detection. In: Proc. of AIRWeb’05, Chiba, Japan (May 2005)
Xue, G.R., et al.: Exploiting the Hierarchical Structure for Link Analysis. In: Proc. of SIGIR’05, Salvador, Brazil (August 2005)
Carvalho, A.L.C., et al.: Site Level Noise Removal for Search Engines. In: Proc. of the World Wide Web conference (May 2006)
Page, L., et al.: The PageRank Citation Ranking: Bringing Order to the Web. Stanford Digital Library Technologies Project (1998)
Gyöngyi, Z., Molina, H.G.: Link Spam Alliances. Technical Report (September 2005)
Ntoulas, A., et al.: Detecting Spam Web Pages through Content Analysis. In: Proc. of the World Wide Web conference (May 2006)
Becchetti, L., et al.: Using Rank Propagation and Probabilistic Counting for Link Based Spam Detection. In: Proc. of WebKDD’06 (August 2006)
Robertson, S.E.: Overview of the Okapi Projects. Journal of Documentation 53(1), 3–7 (1997)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Geng, GG., Wang, CH., Li, QD., Zhu, YP. (2007). Fighting Link Spam with a Two-Stage Ranking Strategy. In: Amati, G., Carpineto, C., Romano, G. (eds) Advances in Information Retrieval. ECIR 2007. Lecture Notes in Computer Science, vol 4425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71496-5_72
Download citation
DOI: https://doi.org/10.1007/978-3-540-71496-5_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71494-1
Online ISBN: 978-3-540-71496-5
eBook Packages: Computer ScienceComputer Science (R0)