Enriching Ontology for Deep Web Search

  • Authors:
  • Yoo Jung An;Soon Ae Chun;Kuo-Chuan Huang;James Geller

  • Affiliations:
  • New Jersey Institute of Technology,;CSI, City University of New York,;New Jersey Institute of Technology,;New Jersey Institute of Technology,

  • Venue:
  • DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
  • Year:
  • 2008

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Abstract

This paper addresses the problems of extracting instances from the Deep Web, enriching a domain specific ontology with those instances, and using this ontology to improve Web search. Extending an existing ontology with a large number of instances extracted from the Deep Web is an important process for making the ontology more usable for indexing of Deep Web sites. We demonstrate how instances extracted from the Deep Web are used to enhance a domain ontology. We show the contribution of the enriched ontology to Web search effectiveness. This is done by comparing the number of relevant Web sites returned by a search engine with a user's search terms only, with the Web sites found when using additional ontology-based search terms. Experiments suggest that the ontology plus instancesapproach results in more relevant Web sites among the first 100 hits.