towards practical abox abduction in large owl dl ontologies

ISCAS OpenIR

	towards practical abox abduction in large owl dl ontologies
	Du Jianfeng; Qi Guilin; Shen Yi-Dong; Pan Jeff Z.
	2011
会议名称	25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11
会议录名称	Proceedings of the National Conference on Artificial Intelligence
页码	1160-1165
会议日期	August 7,
会议地点	San Francisco, CA, United states
收录类别	EI
ISBN	9781577355090
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 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
摘要	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.; 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.
关键词	Artificial Intelligence Data Description Logic Programming Prolog (Programming Language)
主办者	Association for the Advancement of Artificial Intelligence (AAAI); National Science Foundation; AI Journal; Google, Inc.; Microsoft Research
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/16205
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,Shen Yi-Dong,et al. towards practical abox abduction in large owl dl ontologies[C],2011:1160-1165.