Web site traffic ranking estimation via SVM

  • Authors:

  • Peng Ren;Yong Yu

  • Affiliations:

  • Dept. of Computer Science and Engineering, Shanghai Jiao-Tong University, Shanghai, China;Dept. of Computer Science and Engineering, Shanghai Jiao-Tong University, Shanghai, China

  • Venue:
  • ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
  • Year:
  • 2010

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Abstract

Web traffic, one of the most critical factors to measure the quality of one site, is used to express the popularity and importance of Web pages and sites. However, traditional methods, such as PageRank, have poor performances on this measurement. Since it is not easy to get traffic data directly, we decide to find a new method to obtain traffic ranking by machine learning with a few features. In this paper, we collect some common characteristics of Web sites and some data from search engine logs, with analysis and selection, then give a Web site traffic comparison model via SVM. This model can represent the traffic ranking by telling the partial order of any two Web sites. It is shown from experimental results that our model has a better performance than the baseline methods, PageRank and BookRank.