Ontology learning from text: a soft computing paradigm

Chau, Rowena, Smith-Miles, Kate and Yeh, Chung-Hsing 2006, Ontology learning from text: a soft computing paradigm, Lecture notes in computer science, vol. 4234, pp. 295-301.

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Title Ontology learning from text: a soft computing paradigm
Author(s) Chau, Rowena
Smith-Miles, Kate
Yeh, Chung-Hsing
Journal name Lecture notes in computer science
Volume number 4234
Start page 295
End page 301
Publisher Spring-Verlag
Place of publication Heidelberg, Germany
Publication date 2006
ISSN 0302-9743
1611-3349
Summary Text-based information accounts for more than 80% of today’s Web content. They consist of Web pages written in different natural languages. As the semantic Web aims at turning the current Web into a machine-understandable knowledge repository, availability of multilingual ontology thus becomes an issue at the core of a multilingual semantic Web. However, multilingual ontology is too complex and resource intensive to be constructed manually. In this paper, we propose a three-layer model built on top of a soft computing framework to automatically acquire a multilingual ontology from domain specific parallel texts. The objective is to enable semantic smart information access regardless of language over the Semantic Web.
Language eng
Field of Research 080707 Organisation of Information and Knowledge Resources
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2006, Springer-Verlag
Persistent URL http://hdl.handle.net/10536/DRO/DU:30009049

Document type: Journal Article
Collection: School of Engineering and Information Technology
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