Merging techniques for performing data fusion on the web

  • Authors:

  • Theodora Tsikrika;Mounia Lalmas

  • Affiliations:

  • Queen Mary, University of London, London, UK;Queen Mary, University of London, London, UK

  • Venue:
  • Proceedings of the tenth international conference on Information and knowledge management
  • Year:
  • 2001

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Abstract

Data fusion on the Web refers to the merging, into a unified single list, of the ranked document lists, which are retrieved in response to a user query by more than one Web search engine. It is performed by metasearch engines and their merging algorithms utilise the information present in the ranked lists of retrieved documents provided to them by the underlying search engines, such as the rank positions of the retrieved documents and their retrieval scores. In this paper, merging techniques are introduced that take into account not only the rank positions, but also the title and the summary accompanying the retrieved documents. Furthermore, the data fusion process is viewed as being similar to the combination of belief in uncertain reasoning and is modelled using Dempster-Shafer's theory of evidence. Our evaluation experiments indicate that the above merging techniques yield improvements in the effectiveness and that their effectiveness is comparable to that of the approach that merges the ranked lists by downloading and analysing the Web documents.