Citation

• Fast Asynchronous Anti-TrustRank forWeb Spam Detection
  J. Whang, Y. Jung, I. Dhillon, S. Kang, J. Lee.
  WSDM workshop on Misinformation and Misbehavior Mining on the Web (MIS2), 2018.
  
  Bibtex:
  
  @article{whang2018fastasync, author = "Joyce Whang AND Yeonsung Jung AND Inderjit S. Dhillon AND Seonggoo Kang AND Jungmin Lee", title = "Fast Asynchronous Anti-TrustRank forWeb Spam Detection", year = "2018", abstract = "Web spam detection is an important problem in Web search. Since Web spam pages tend to have a lot of spurious links, many Web spam detection algorithms exploit the hyperlink structure between the Web pages to detect the spam pages. Anti-TrustRank algorithm is a well-known link-based spam detection algorithm which follows the principle that spam pages are likely to be referenced by other spam pages. Since a real-world Web graph involves tens of billions of nodes, it is crucial to develop work-efficient Web spam detection algorithms. In this paper, we develop asynchronous Anti-TrustRank algorithms which allow us to significantly reduce the number of arithmetic operations compared to the traditional synchronous Anti-TrustRank algorithm without degrading the performance in detecting Web spams. We theoretically prove the convergence of the asynchronous Anti-TrustRank algorithms, and conduct experiments on a real-world Web graph indexed by NAVER which is the most popular search engine in Korea." }