ISCAS OpenIR
A graph derivation based approach for measuring and comparing structural semantics of ontologies
Ma, Yinglong (1); Liu, Ling (2); Lu, Ke (3); Jin, Beihong (4); Liu, Xiangjie (1)
2014
SourceIEEE Transactions on Knowledge and Data Engineering
ISSN10414347
Volume26Issue:5Pages:1039-1052
English AbstractOntology 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.; 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.
Indexed TypeSCI ; EI
KeywordOntology Ontology Measures Ontology Comparison Ontology Reuse
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
Language英语
WOS IDWOS:000337965900001
Citation statistics
Content Type期刊论文
URIhttp://ir.iscas.ac.cn/handle/311060/16698
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
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,2014,26(5):1039-1052.
APA Ma, Yinglong ,Liu, Ling ,Lu, Ke ,Jin, Beihong ,&Liu, Xiangjie .(2014).A graph derivation based approach for measuring and comparing structural semantics of ontologies.IEEE Transactions on Knowledge and Data Engineering,26(5),1039-1052.
MLA Ma, Yinglong ,et al."A graph derivation based approach for measuring and comparing structural semantics of ontologies".IEEE Transactions on Knowledge and Data Engineering 26.5(2014):1039-1052.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Ma, Yinglong (1)]'s Articles
[Liu, Ling (2)]'s Articles
[Lu, Ke (3)]'s Articles
Baidu academic
Similar articles in Baidu academic
[Ma, Yinglong (1)]'s Articles
[Liu, Ling (2)]'s Articles
[Lu, Ke (3)]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Ma, Yinglong (1)]'s Articles
[Liu, Ling (2)]'s Articles
[Lu, Ke (3)]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.