approximating linear order inference in owl 2 dl by horn compilation

ISCAS OpenIR

	approximating linear order inference in owl 2 dl by horn compilation
	Du Jianfeng; Qi Guilin; Pan Jeff Z.; Shen Yi-Dong
	2012
会议名称	2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012
会议录名称	Proceedings - 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012
页码	97-104
会议日期	December 4, 2012 - December 7, 2012
会议地点	Macau, China
收录类别	EI
ISBN	9780769548807
部门归属	(1) Guangdong University of Foreign Studies Guangzhou 510006 China; (2) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China; (3) School of Computer Science and Engineering Southeast University NanJing 211189 China; (4) Department of Computing Science University of Aberdeen Aberdeen AB243UE United Kingdom
摘要	In order to directly reason over inconsistent OWL 2 DL ontologies, this paper considers linear order inference which comes from propositional logic. Consequences of this inference in an inconsistent ontology are defined as consequences in a certain consistent sub-ontology. This paper proposes a novel framework for compiling an OWL 2 DL ontology to a Horn propositional program so that the intended consistent sub-ontology for linear order inference can be approximated from the compiled result in polynomial time. A tractable method is proposed to realize this framework. It guarantees that the compiled result has a polynomial size. Experimental results show that the proposed method computes the exact intended sub-ontology for almost all test cases, while it is significantly more efficient and scalable than state-of-the-art exact methods. © 2012 IEEE.; In order to directly reason over inconsistent OWL 2 DL ontologies, this paper considers linear order inference which comes from propositional logic. Consequences of this inference in an inconsistent ontology are defined as consequences in a certain consistent sub-ontology. This paper proposes a novel framework for compiling an OWL 2 DL ontology to a Horn propositional program so that the intended consistent sub-ontology for linear order inference can be approximated from the compiled result in polynomial time. A tractable method is proposed to realize this framework. It guarantees that the compiled result has a polynomial size. Experimental results show that the proposed method computes the exact intended sub-ontology for almost all test cases, while it is significantly more efficient and scalable than state-of-the-art exact methods. © 2012 IEEE.
关键词	Data Description Polynomial Approximation
主办者	IEEE
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/15949
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Du Jianfeng,Qi Guilin,Pan Jeff Z.,et al. approximating linear order inference in owl 2 dl by horn compilation[C],2012:97-104.