Automated Chinese Domain Ontology Construction from Text Documents

Ontology as an important knowledge representation tool is widely used in many fields. Constructing domain ontology is a lengthy, costly task. Rapid, accurate construction of ontology has thus become an important topic. In this paper, a method that automates construction of the ontology is proposed. The method integrates text analysis, TF/IDF calculation, association rules extraction, pattern rules matching and RDF technologies. The ontology construction method does not require expenditure of time to select keywords and to define the relations by human edit or expert assistance. The method facilitates user understanding of the content of data and its relevancy, and is able to suggest content that is highly relevant. Experimental results show that the proposed approach can effectively construct Chinese domain ontology from text documents.

[1]  Brian R. Gaines,et al.  Comparing conceptual structures: consensus, conflict, correspondence and contrast , 1989 .

[2]  Steffen Staab,et al.  Ontology Learning for the Semantic Web , 2002, IEEE Intell. Syst..

[3]  David E. Millard,et al.  Automatic Ontology-Based Knowledge Extraction from Web Documents , 2003, IEEE Intell. Syst..

[4]  Lee Gillam,et al.  Terminology and the construction of ontology , 2005 .

[5]  Carole D. Hafner,et al.  The State of the Art in Ontology Design: A Survey and Comparative Review , 1997, AI Mag..

[6]  Joel D. Martin,et al.  Getting to the (c)ore of knowledge: mining biomedical literature , 2002, Int. J. Medical Informatics.

[7]  Ramakrishnan Srikant,et al.  Mining generalized association rules , 1995, Future Gener. Comput. Syst..

[8]  Yu-Liang Chi.  Elicitation synergy of extracting conceptual tags and hierarchies in textual document , 2007, Expert Syst. Appl..

[9]  N. Guarino,et al.  Formal Ontology in Information Systems : Proceedings of the First International Conference(FOIS'98), June 6-8, Trento, Italy , 1998 .

[10]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[11]  Paola Velardi,et al.  Using text processing techniques to automatically enrich a domain ontology , 2001, FOIS.

[12]  Arno Scharl,et al.  Mining large samples of web-based corpora , 2004, Knowl. Based Syst..

[13]  Rung Ching Chen,et al.  Using recursive ART network to construction domain ontology based on term frequency and inverse document frequency , 2008, Expert Syst. Appl..

[14]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .

[15]  Asunción Gómez-Pérez,et al.  Ontology Specification Languages for the Semantic Web , 2002, IEEE Intell. Syst..