stable cohesion metrics for evolving ontologies

ISCAS OpenIR

	stable cohesion metrics for evolving ontologies
	Ma Yinglong; Wu Haijiang; Ma Xinyu; Jin Beihong; Huang Tao; Wei Jun
	2011
发表期刊	Journal of Software Maintenance and Evolution
ISSN	1532-060X
卷号	23 期号:5 页码:343-359
摘要	With the drastic development of semantic-driven applications, assessing the quality of ontologies has received more attention. Measuring and assessing the quality of ontologies can help ontology engineers to control project management and reduce the risk of project failures. However, most of the existing ontology metrics for measuring and assessing the quality of ontologies are defined based on ontology structure, and neglect the stability of ontology measurement. In this paper, we concentrate on stable ontology measurement by using semantically derived ontology metrics. We propose four ontology cohesion metrics, which fully consider the implicitly expressed semantic information and are defined based on ontological semantics rather than ontology structure. Before measuring and assessing an ontology, we materialize a pre-processing for stable ontology measurement by treating the ontology. The proposed ontology cohesion metrics are theoretically validated by the validation criteria of object-oriented software. The experimental results show that we can successfully collect more semantic knowledge from the testing ontologies for stable ontology measurement by using the proposed ontology cohesion metrics. The ontology cohesion metrics proposed in this paper can be reasonably used as a cogent complementarity of existing ontology metrics. © 2010 John Wiley & Sons, Ltd.; With the drastic development of semantic-driven applications, assessing the quality of ontologies has received more attention. Measuring and assessing the quality of ontologies can help ontology engineers to control project management and reduce the risk of project failures. However, most of the existing ontology metrics for measuring and assessing the quality of ontologies are defined based on ontology structure, and neglect the stability of ontology measurement. In this paper, we concentrate on stable ontology measurement by using semantically derived ontology metrics. We propose four ontology cohesion metrics, which fully consider the implicitly expressed semantic information and are defined based on ontological semantics rather than ontology structure. Before measuring and assessing an ontology, we materialize a pre-processing for stable ontology measurement by treating the ontology. The proposed ontology cohesion metrics are theoretically validated by the validation criteria of object-oriented software. The experimental results show that we can successfully collect more semantic knowledge from the testing ontologies for stable ontology measurement by using the proposed ontology cohesion metrics. The ontology cohesion metrics proposed in this paper can be reasonably used as a cogent complementarity of existing ontology metrics. © 2010 John Wiley & Sons, Ltd.
收录类别	EI ; SCI
关键词	Adhesion Project Management Semantics
部门归属	(1) School of Control and Computer Engineering North China Electric Power University Beijing 102206 China; (2) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100190 China
学科领域	Computer Science
资助者	Chinese National '863' High-Tech Program2007AA04Z148; State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of SciencesSYSKF1010; Fundamental Research Funds for the Central Universities
语种	英语
WOS记录号	WOS:000293456600002
引用统计
内容类型	期刊论文
URI标识	http://ir.iscas.ac.cn/handle/311060/16014
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Ma Yinglong,Wu Haijiang,Ma Xinyu,et al. stable cohesion metrics for evolving ontologies[J]. Journal of Software Maintenance and Evolution,2011,23(5):343-359.
APA	Ma Yinglong,Wu Haijiang,Ma Xinyu,Jin Beihong,Huang Tao,&Wei Jun.(2011).stable cohesion metrics for evolving ontologies.Journal of Software Maintenance and Evolution,23(5),343-359.
MLA	Ma Yinglong,et al."stable cohesion metrics for evolving ontologies".Journal of Software Maintenance and Evolution 23.5(2011):343-359.