Conference Proceedings

Ontology learning from text: A soft computing paradigm

Rowena Chau, Kate Smith-Miles, Chung-Hsing Yeh, I King (ed.), J Wang (ed.), L Chan (ed.), DL Wang (ed.)

NEURAL INFORMATION PROCESSING, PT 3, PROCEEDINGS | SPRINGER-VERLAG BERLIN | Published : 2006

Abstract

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 langu..

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University of Melbourne Researchers