CONQUER: A methodology for context-aware query processing on the World Wide Web

Storey, Veda C., Burton-Jones, Andrew, Sugurnaran, Vijayan and Purao, Sandeep (2008) CONQUER: A methodology for context-aware query processing on the World Wide Web. Information Systems Research, 19 1: 3-25. doi:10.1287/isre.1070.0140

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads

Author Storey, Veda C.
Burton-Jones, Andrew
Sugurnaran, Vijayan
Purao, Sandeep
Title CONQUER: A methodology for context-aware query processing on the World Wide Web
Journal name Information Systems Research   Check publisher's open access policy
ISSN 1047-7047
Publication date 2008-03
Sub-type Article (original research)
DOI 10.1287/isre.1070.0140
Open Access Status
Volume 19
Issue 1
Start page 3
End page 25
Total pages 23
Place of publication Hanover, MD, United States
Publisher Institute for Operations Research and the Management Sciences
Language eng
Abstract A major impediment to accurate information retrieval from the World Wide Web is the inability of search engines to incorporate semantics in the search process. This research presents a methodology, CONQUER (CONtext-aware QUERy processing), that enhances the semantic content of Web queries using two complementary knowledge sources: lexicons and ontologies. The methodology constructs a semantic net using the original query as a seed, and refines the net with terms from the two knowledge sources. The enhanced query, represented by the refined semantic net, can be executed by search engines. This paper describes the methodology and its implementation in a prototype. An empirical evaluation shows that queries suggested by the prototype produce more relevant results than those obtained by the original queries. The research, thus, provides a successful demonstration of the use of existing knowledge sources to enhance the semantic content of Web queries. The paper concludes by identifying potential uses of such enhancements of search technology in organizational contexts.
Keyword Query augmentation
Semantic retrieval
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: UQ Business School Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 14 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 31 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Thu, 28 Jun 2012, 17:23:40 EST by Karen Morgan on behalf of UQ Business School