Enriching ontology for deep web search

Yoo Jung An, Soon Ae Chun, Kuo Chuan Huang, James Geller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations


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 instances approach results in more relevant Web sites among the first 100 hits.

Original languageEnglish (US)
Title of host publicationDatabase and Expert Systems Applications - 19th International Conference, DEXA 2008, Proceedings
Number of pages8
StatePublished - 2008
Event19th International Conference on Database and Expert Systems Applications, DEXA 2008 - Turin, Italy
Duration: Sep 1 2008Sep 5 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5181 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other19th International Conference on Database and Expert Systems Applications, DEXA 2008

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


  • Deep Web
  • Domain Ontology
  • Instance Extraction
  • Semantic Web


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