Research Papers

A Framework to Normalize Ontology Representation for Stable Measurement

[+] Author and Article Information
Yinglong Ma

Associate Professor
Control and Computer Engineering,
North China Electric Power University,
Beijing 102206, China

Chunlong Wang

Control and Computer Engineering,
North China Electric Power University,
Beijing 102206, China
e-mail: wang_cl15@163.com

Beihong Jin

Technology Center of Software Engineering,
Institute of Software,
Chinese Academy of Sciences,
Beijing 100190, China
e-mail: jbh@otcaix.iscas.ac.cn

1Corresponding author.

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received September 7, 2012; final manuscript received June 2, 2015; published online August 3, 2015. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 15(4), 041001 (Aug 03, 2015) (7 pages) Paper No: JCISE-12-1148; doi: 10.1115/1.4031011 History: Received September 07, 2012

Ontology measurement is an important challenge in the field of knowledge management in order to manage the development of ontology based systems and reduce the risk of project failure. Effective ontology measurement is the precondition on which the meaningful and useful ontology evaluation can be made. We propose a framework to normalize representation of ontologies for their stable measurement, where the semantic enriched representation model (SERM) is proposed as the unique representation for ontologies. By the normalization framework, we provide a four-step procedure to extract ontology entities and calculate measures based on SERM model. Both the theoretical analysis and the experimental results show that our framework is effective and useful to perform stable ontology measurement. It is suitable to measure more expressive ontologies. This framework enables users to perform automatic ontology measurement without much expertise knowledge about ontology programming and reasoning.

Copyright © 2015 by ASME
Topics: Ontologies
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Fig. 1

An ontology example with atomic and complex concepts

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Fig. 2

Graph-based ontology representations

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Fig. 3

The overview of framework

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Fig. 4

The SERM model representations




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