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Title:
A graph derivation based approach for measuring and comparing structural semantics of ontologies
Author: Ma, Yinglong (1) ; Liu, Ling (2) ; Lu, Ke (3) ; Jin, Beihong (4) ; Liu, Xiangjie (1)
Keyword: Ontology ; ontology measures ; ontology comparison ; ontology reuse
Source: IEEE Transactions on Knowledge and Data Engineering
Issued Date: 2014
Volume: 26, Issue:5, Pages:1039-1052
Indexed Type: SCI ; EI
Department: (1) School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; (2) College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, United States; (3) University of Chinese Academy of Sciences, Beijing 100049, China; (4) Technology Center of Software Engineering, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
Abstract: Ontology reuse offers great benefits by measuring and comparing ontologies. However, the state of art approaches for measuring ontologies neglects the problems of both the polymorphism of ontology representation and the addition of implicit semantic knowledge. One way to tackle these problems is to devise a mechanism for ontology measurement that is stable, the basic criteria for automatic measurement. In this paper, we present a graph derivation representation based approach (GDR) for stable semantic measurement, which captures structural semantics of ontologies and addresses those problems that cause unstable measurement of ontologies. This paper makes three original contributions. First, we introduce and define the concept of semantic measurement and the concept of stable measurement. We present the GDR based approach, a three-phase process to transform an ontology to its GDR. Second, we formally analyze important properties of GDRs based on which stable semantic measurement and comparison can be achieved successfully. Third but not the least, we compare our GDR based approach with existing graph based methods using a dozen real world exemplar ontologies. Our experimental comparison is conducted based on nine ontology measurement entities and distance metric, which stably compares the similarity of two ontologies in terms of their GDRs. Copyright © 2013 IEEE.
English Abstract: Ontology reuse offers great benefits by measuring and comparing ontologies. However, the state of art approaches for measuring ontologies neglects the problems of both the polymorphism of ontology representation and the addition of implicit semantic knowledge. One way to tackle these problems is to devise a mechanism for ontology measurement that is stable, the basic criteria for automatic measurement. In this paper, we present a graph derivation representation based approach (GDR) for stable semantic measurement, which captures structural semantics of ontologies and addresses those problems that cause unstable measurement of ontologies. This paper makes three original contributions. First, we introduce and define the concept of semantic measurement and the concept of stable measurement. We present the GDR based approach, a three-phase process to transform an ontology to its GDR. Second, we formally analyze important properties of GDRs based on which stable semantic measurement and comparison can be achieved successfully. Third but not the least, we compare our GDR based approach with existing graph based methods using a dozen real world exemplar ontologies. Our experimental comparison is conducted based on nine ontology measurement entities and distance metric, which stably compares the similarity of two ontologies in terms of their GDRs. Copyright © 2013 IEEE.
Language: 英语
WOS ID: WOS:000337965900001
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/16698
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Ma, Yinglong ,Liu, Ling ,Lu, Ke ,et al. A graph derivation based approach for measuring and comparing structural semantics of ontologies[J]. IEEE Transactions on Knowledge and Data Engineering,2014-01-01,26(5):1039-1052.
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