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| approximating linear order inference in owl 2 dl by horn compilation | |
| Du Jianfeng; Qi Guilin; Pan Jeff Z.; Shen Yi-Dong | |
| 2012 | |
| Conference Name | 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012 |
| Source | Proceedings - 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012 |
| Pages | 97-104 |
| Conference Date | December 4, 2012 - December 7, 2012 |
| Conference Place | Macau, China |
| 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 |
| 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.; 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. |
| Keyword | Data Description Polynomial Approximation |
| Sponsorship | IEEE |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/15949 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation 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. |
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