The central problem of automatic retrieval from unformatted text is that computational devices are not adequately trained to look for associated information. However for complete understanding and information retrieval, a complete artificial intelligence would have to be built. This paper describes a method for achieving significant information retrieval by using a semantic search engine. The underlying semantic information is stored in a network of clarified words, linked by logical connections. We employ simple scoring techniques on collections of paths in this network to establish a degree of relevance between a document and a clarified search criterion. This technique has been applied with success to test examples and can be easily scaled up to search large documents.
History
Event
Australian Document Computing Symposium (3rd : 1998 : Sydney, N. S. W.)
Pagination
47 - 53
Publisher
University of Sydney, Basser Department of Computer Science
Location
Sydney, N. S. W.
Place of publication
Sydney, N. S. W.
Start date
1998-08-20
ISBN-10
186487001X
Language
eng
Notes
Every reasonable effort has been made to ensure that permission has been obtained for items included in Deakin Research Online. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au
Publication classification
E1.1 Full written paper - refereed
Copyright notice
1998, University of Sydney, Basser Department of Computer Science
Editor/Contributor(s)
J Kay, M Milosavljevic
Title of proceedings
Proceedings of ADCS '98 : Third Australian Document Computing Symposium