Using anchor text for homepage and topic distillation search tasks

  • Authors:

  • Mingfang Wu;David Hawking;Andrew Turpin;Falk Scholer

  • Affiliations:

  • School of Computer Science and Information Technology, RMIT University, Melbourne, Australia;Funnelback Pty Ltd, Australia and Research School of Computer Science, Australian National University;Department of Computer Science and Software Engineering, University of Melbourne, Australia;School of Computer Science and Information Technology, RMIT University, Melbourne, Australia

  • Venue:
  • Journal of the American Society for Information Science and Technology
  • Year:
  • 2012

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Abstract

Past work suggests that anchor text is a good source of evidence that can be used to improve web searching. Two approaches for making use of this evidence include fusing search results from an anchor text representation and the original text representation based on a document's relevance score or rank position, and combining term frequency from both representations during the retrieval process. Although these approaches have each been tested and compared against baselines, different evaluations have used different baselines; no consistent work enables rigorous cross-comparison between these methods. The purpose of this work is threefold. First, we survey existing fusion methods of using anchor text in search. Second, we compare these methods with common testbeds and web search tasks, with the aim of identifying the most effective fusion method. Third, we try to correlate search performance with the characteristics of a test collection. Our experimental results show that the best performing method in each category can significantly improve search results over a common baseline. However, there is no single technique that consistently outperforms competing approaches across different collections and search tasks. © 2012 Wiley Periodicals, Inc.