Automated ontology construction for unstructured text documents

Chang Shing Lee, Yuan Fang Kao, Yau Hwang Kuo, Mei Hui Wang

Research output: Contribution to journalArticlepeer-review

154 Citations (Scopus)


Ontology is playing an increasingly important role in knowledge management and the Semantic Web. This study presents a novel episode-based ontology construction mechanism to extract domain ontology from unstructured text documents. Additionally, fuzzy numbers for conceptual similarity computing are presented for concept clustering and taxonomic relation definitions. Moreover, concept attributes and operations can be extracted from episodes to construct a domain ontology, while non-taxonomic relations can be generated from episodes. The fuzzy inference mechanism is also applied to obtain new instances for ontology learning. Experimental results show that the proposed approach can effectively construct a Chinese domain ontology from unstructured text documents.

Original languageEnglish
Pages (from-to)547-566
Number of pages20
JournalData and Knowledge Engineering
Issue number3
Publication statusPublished - 2007 Mar

All Science Journal Classification (ASJC) codes

  • Information Systems and Management


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