Incorporating web browsing activities into anchor texts for web search

  • Authors:

  • Bo Zhou;Yiqun Liu;Min Zhang;Yijiang Jin;Shaoping Ma

  • Affiliations:

  • State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, CS&T Department, Tsinghua University, Beijing, People's Republic of ...;State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, CS&T Department, Tsinghua University, Beijing, People's Republic of ...;State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, CS&T Department, Tsinghua University, Beijing, People's Republic of ...;State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, CS&T Department, Tsinghua University, Beijing, People's Republic of ...;State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, CS&T Department, Tsinghua University, Beijing, People's Republic of ...

  • Venue:
  • Information Retrieval
  • Year:
  • 2011

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Abstract

Anchor texts complement Web page content and have been used extensively in commercial Web search engines. Existing methods for anchor text weighting rely on the hyperlink information which is created by page content editors. Since anchor texts are created to help user browse the Web, browsing behavior of Web users may also provide useful or complementary information for anchor text weighting. In this paper, we discuss the possibility and effectiveness of incorporating browsing activities of Web users into anchor texts for Web search. We first make an analysis on the effectiveness of anchor texts with browsing activities. And then we propose two new anchor models which incorporate browsing activities. To deal with the data sparseness problem of user-clicked anchor texts, two features of user's browsing behavior are explored and analyzed. Based on these features, a smoothing method for the new anchor models is proposed. Experimental results show that by incorporating browsing activities the new anchor models outperform the state-of-art anchor models which use only the hyperlink information. This study demonstrates the benefits of Web browsing activities to affect anchor text weighting.