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Title:
approximating linear order inference in owl 2 dl by horn compilation
Author: Du Jianfeng ; Qi Guilin ; Pan Jeff Z. ; Shen Yi-Dong
Source: Proceedings - 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012
Conference Name: 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012
Conference Date: December 4, 2012 - December 7, 2012
Issued Date: 2012
Conference Place: Macau, China
Keyword: Data description ; Polynomial approximation
Indexed Type: EI
ISBN: 9780769548807
Department: (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
Sponsorship: IEEE
Abstract: 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.
English Abstract: 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.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15949
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Du Jianfeng,Qi Guilin,Pan Jeff Z.,et al. approximating linear order inference in owl 2 dl by horn compilation[C]. 见:2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012. Macau, China. December 4, 2012 - December 7, 2012.
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