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A spamicity approach to web spam detection

Publication ,  Conference
Zhou, B; Pei, J; Tang, Z
Published in: Society for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130
January 1, 2008

Web spam, which refers to any deliberate actions bringing to selected web pages an unjustifiable favorable relevance or importance, is one of the major obstacles for high quality information retrieval on the web. Most of the existing web spam detection methods are supervised that require a large and representative training set of web pages. Moreover, they often assume some global information such as a large web graph and snapshots of a large collection of web pages. However, in many situations such assumptions may not hold. In this paper, we study the problem of unsupervised web spam detection. We introduce the notion of spamicity to measure how likely a page is spam. Spamicity is a more flexible and user-controllable measure than the traditional supervised classification methods. We propose efficient online link spam and term spam detection methods using spamicity. Our methods do not need training and are cost effective. A real data set is used to evaluate the effectiveness and the efficiency of our methods. Copyright © by SIAM.

Duke Scholars

Published In

Society for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130

DOI

ISBN

9781605603179

Publication Date

January 1, 2008

Volume

1

Start / End Page

277 / 288
 

Citation

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Zhou, B., Pei, J., & Tang, Z. (2008). A spamicity approach to web spam detection. In Society for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130 (Vol. 1, pp. 277–288). https://doi.org/10.1137/1.9781611972788.25
Zhou, B., J. Pei, and Z. Tang. “A spamicity approach to web spam detection.” In Society for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130, 1:277–88, 2008. https://doi.org/10.1137/1.9781611972788.25.
Zhou B, Pei J, Tang Z. A spamicity approach to web spam detection. In: Society for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130. 2008. p. 277–88.
Zhou, B., et al. “A spamicity approach to web spam detection.” Society for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130, vol. 1, 2008, pp. 277–88. Scopus, doi:10.1137/1.9781611972788.25.
Zhou B, Pei J, Tang Z. A spamicity approach to web spam detection. Society for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130. 2008. p. 277–288.

Published In

Society for Industrial and Applied Mathematics - 8th SIAM International Conference on Data Mining 2008, Proceedings in Applied Mathematics 130

DOI

ISBN

9781605603179

Publication Date

January 1, 2008

Volume

1

Start / End Page

277 / 288