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.
A Framework to Normalize Ontology Representation for Stable Measurement
Control and Computer Engineering,
North China Electric Power University,
Beijing 102206, China
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.
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Ma, Y., Wang, C., and Jin, B. (August 3, 2015). "A Framework to Normalize Ontology Representation for Stable Measurement." ASME. J. Comput. Inf. Sci. Eng. December 2015; 15(4): 041001. https://doi.org/10.1115/1.4031011
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