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Title:
towards practical abox abduction in large owl dl ontologies
Author: Du Jianfeng ; Qi Guilin ; Shen Yi-Dong ; Pan Jeff Z.
Source: Proceedings of the National Conference on Artificial Intelligence
Conference Name: 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11
Conference Date: August 7,
Issued Date: 2011
Conference Place: San Francisco, CA, United states
Keyword: Artificial intelligence ; Data description ; Logic programming ; PROLOG (programming language)
Indexed Type: EI
ISBN: 9781577355090
Department: (1) Guangdong University of Foreign Studies Guangzhou 510006 China; (2) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China; (3) School of Computer Science and Engineering Southeast University NanJing 211189 China; (4) State Key Laboratory for Novel Software Technology Nanjing University China; (5) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100190 China; (6) Department of Computing Science University of Aberdeen Aberdeen AB243UE United Kingdom
Sponsorship: Association for the Advancement of Artificial Intelligence (AAAI); National Science Foundation; AI Journal; Google, Inc.; Microsoft Research
Abstract: ABox abduction is an important aspect for abductive reasoning in Description Logics (DLs). It finds all minimal sets of ABox axioms that should be added to a background ontology to enforce entailment of a specified set of ABox axioms. As far as we know, by now there is only one ABox abduction method in expressive DLs computing abductive solutions with certain minimality. However, the method targets an ABox abduction problem that may have infinitely many abductive solutions and may not output an abductive solution in finite time. Hence, in this paper we propose a new ABox abduction problem which has only finitely many abductive solutions and also propose a novel method to solve it. The method reduces the original problem to an abduction problem in logic programming and solves it with Prolog engines. Experimental results show that the method is able to compute abductive solutions in benchmark OWL DL ontologies with large ABoxes. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved.
English Abstract: ABox abduction is an important aspect for abductive reasoning in Description Logics (DLs). It finds all minimal sets of ABox axioms that should be added to a background ontology to enforce entailment of a specified set of ABox axioms. As far as we know, by now there is only one ABox abduction method in expressive DLs computing abductive solutions with certain minimality. However, the method targets an ABox abduction problem that may have infinitely many abductive solutions and may not output an abductive solution in finite time. Hence, in this paper we propose a new ABox abduction problem which has only finitely many abductive solutions and also propose a novel method to solve it. The method reduces the original problem to an abduction problem in logic programming and solves it with Prolog engines. Experimental results show that the method is able to compute abductive solutions in benchmark OWL DL ontologies with large ABoxes. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/16205
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Du Jianfeng,Qi Guilin,Shen Yi-Dong,et al. towards practical abox abduction in large owl dl ontologies[C]. 见:25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11. San Francisco, CA, United states. August 7,.
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