A Semantic-Oriented Method for Ontology Merging

Article Preview

Abstract:

Most of the methods for ontology merging need participation of domain experts and provide only partial automation with low efficiency. It is time-consuming and laborious especially when large amount of data are to be merged. In this paper, a method based on semantic is designed for ontology merging according to the case of ontologies to be merged. In this method, first the ontologies to be merged are conversed into a unified format. Then a secondary file is generated. After that semantic analysis is applied to secondary file and a dynamic SQL statements is generated automatically. At last the SQL statements are executed to finish ontology merging. It has been proved by the experiment that using this method would get good precision and high efficiency. Using this method, two ontologies Chinese Agricultural Thesaurus and AGROVOC of the Food and Agriculture Organization are merged successfully.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1347-1351

Citation:

Online since:

December 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Natalya,Fridman Noy and Mark A.Musen,SMART:Automated Support for Ontology Merging and Alignment",Stanford Medical Informatics Stanford University.

Google Scholar

[2] Stumme . G and Madche . A.FCA-Merge:Bottom—up merging of ontologies.In 7th. international Conference on Artificial Intelligence(IJCAl01),pages 225—230,Seattle,WA, 2001.

Google Scholar

[3] A. C. LIANG and M. SINI. Mapping AGROVOC and the Chinese Agricultural Thesaurus: Definitions, tools, procedures. New Review of Hypermedia and Multimedia, Vol. 12, No. 1, June 2006, 51_62.

DOI: 10.1080/13614560600774396

Google Scholar

[4] YANG Xian-di, HE Ning, WU Li-bing. Ontology Integration Description Based on Category Theory. Computer Engineering, 2009,35(6):76—78.

Google Scholar

[5] Wanlin Gao. Research and Design of the Agricultural Short-Message Management System. Computer And Computing Technologies In Agriculture, Volume II. 2008/3/25Volume 259/2008 pp.833-840.

Google Scholar

[6] Wanlin Gao. Design of Voice Service System for Agricultural Keywords Recognition. 2010 World Automation Congress, WAC 2010. 2010Volume23, pp.477-82.

Google Scholar