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Title:
A Framework to Normalize Ontology Representation for Stable Measurement
Author: Ma, YL ; Wang, CL ; Jin, BH
Source: JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING
Issued Date: 2015
Volume: 15, Issue:4
Indexed Type: SCI
Department: North China Elect Power Univ, Control & Comp Engn, Beijing 102206, Peoples R China. Chinese Acad Sci, Inst Software, Technol Ctr Software Engn, Beijing 100190, Peoples R China.
Abstract: 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.
English Abstract: 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.
Language: 英语
WOS ID: WOS:000365270500001
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Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/17429
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Ma, YL,Wang, CL,Jin, BH. A Framework to Normalize Ontology Representation for Stable Measurement[J]. JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING,2015-01-01,15(4).
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