Searching the hypermedia web: improved topic distillation through network analytic relevance ranking

  • Authors:

  • Behnak Yaltaghian;Mark Chignell

  • Affiliations:

  • Department of Mechanical and Industrial Engineering, and Knowledge Media Design Institute, Bahen Centre for Information Technology, University of Toronto, Canada M5S 2E4;Department of Mechanical and Industrial Engineering, and Knowledge Media Design Institute, Bahen Centre for Information Technology, University of Toronto, Canada M5S 2E4

  • Venue:
  • The New Review of Hypermedia and Multimedia - Hypermedia and the world wide web
  • Year:
  • 2003

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Abstract

The Web is a large hypermedia space that is generally explored using search engines. These search engines are evolving to make more effective use of the hypermedia structure of the Web. This paper contributes to this evolution by proposing new methods of topic distillation in structured search based on co-citation and network analysis. We describe a set of 21 network analysis measures of relevance in Web search output. These measures are then compared with human judgments in two studies. In the first study, we compare the average judged relevance of the top 20 search results selected by Google vs. the top 20 results as selected by each of the 21 network analysis measures. All but one of the network analysis measures ("inlink") showed significantly (p