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, doi: 10.1007/11893295_34.

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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
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
DOI 10.1007/11893295_34
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

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