Measuring ontology information by rules based transformation

ISCAS OpenIR

	Measuring ontology information by rules based transformation
	Ma, Yinglong (1); Lu, Ke (3); Zhang, Ying (1); Jin, Beihong (2); Ma, Y.(yinglongma@gmail.com)
	2013
发表期刊	Knowledge-Based Systems
ISSN	9507051
卷号	50 页码:234-245
摘要	Ontologies have currently attracted much attention of researchers and engineers in many fields such as knowledge management, etc. It is attractive for ontology engineers to select and reuse the existing ontologies by measuring and evaluating them because ontology construction is rather tedious and costly. In this paper, a general framework for stable semantic ontology measurement is proposed. We first clarify the concepts of syntactic, semantic and stable semantic ontology measurement. Then we present the semantic derived model (SDM) to represent the semantic model of an ontology. By rule based transformation, an ontology can be automatically transformed into its final semantic derived model (FSDM) which is unique. Furthermore, we can measure ontologies based on FSDM by analyzing the types of entities of the existing ontology metrics. The related experiments are made to illustrate that our framework can effectively excavate and stably measure the semantics of ontologies. © 2013 Elsevier B.V. All rights reserved.; Ontologies have currently attracted much attention of researchers and engineers in many fields such as knowledge management, etc. It is attractive for ontology engineers to select and reuse the existing ontologies by measuring and evaluating them because ontology construction is rather tedious and costly. In this paper, a general framework for stable semantic ontology measurement is proposed. We first clarify the concepts of syntactic, semantic and stable semantic ontology measurement. Then we present the semantic derived model (SDM) to represent the semantic model of an ontology. By rule based transformation, an ontology can be automatically transformed into its final semantic derived model (FSDM) which is unique. Furthermore, we can measure ontologies based on FSDM by analyzing the types of entities of the existing ontology metrics. The related experiments are made to illustrate that our framework can effectively excavate and stably measure the semantics of ontologies. © 2013 Elsevier B.V. All rights reserved.
收录类别	SCI ; EI
关键词	Ontology Ontology Measurement Stable Measurement Semantic Measurement Ontology Engineering
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; (3) University of Chinese Academy of Sciences, Beijing 100049, China
语种	英语
WOS记录号	WOS:000323875500018
引用统计
内容类型	期刊论文
URI标识	http://ir.iscas.ac.cn/handle/311060/16916
专题	中国科学院软件研究所
通讯作者	Ma, Y.(yinglongma@gmail.com)
推荐引用方式 GB/T 7714	Ma, Yinglong ,Lu, Ke ,Zhang, Ying ,et al. Measuring ontology information by rules based transformation[J]. Knowledge-Based Systems,2013,50:234-245.
APA	Ma, Yinglong ,Lu, Ke ,Zhang, Ying ,Jin, Beihong ,&Ma, Y..(2013).Measuring ontology information by rules based transformation.Knowledge-Based Systems,50,234-245.
MLA	Ma, Yinglong ,et al."Measuring ontology information by rules based transformation".Knowledge-Based Systems 50(2013):234-245.