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A tractable approach to ABox abduction over description logic ontologies
Du, Jianfeng (1); Wang, Kewen (2); Shen, Yi-Dong (3); Du, Jianfeng
2014
Conference Name28th AAAI Conference on Artificial Intelligence, AAAI 2014, 26th Innovative Applications of Artificial Intelligence Conference, IAAI 2014 and the 5th Symposium on Educational Advances in Artificial Intelligence, EAAI 2014
Pages1034-1040
Conference DateJuly 27, 2014 - July 31, 2014
Conference PlaceQuebec City, QC, Canada
Indexed TypeEI
Publish PlaceAI Access Foundation
ISBN9781577356783
Department(1) Guangdong University of Foreign Studies, Guangzhou, China; (2) Griffith University, Brisbane; QLD, Australia; (3) State Key Laboratory Of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China
English AbstractABox abduction is an important reasoning mechanism for description logic ontologies. It computes all minimal explanations (sets of ABox assertions) whose appending to a consistent ontology enforces the entailment of an observation while keeps the ontology consistent. We focus on practical computation for a general problem of ABox abduction, called the query abduction problem, where an observation is a Boolean conjunctive query and the explanations may contain fresh individuals neither in the ontology nor in the observation. However, in this problem there can be infinitely many minimal explanations. Hence we first identify a class of TBoxes called first-order rewritable TBoxes. It guaran-tees the existence of finitely many minimal explanations and is sufficient for many ontology applications. To reduce the number of explanations that need to be computed, we introduce a special kind of minimal explanations called representative explanations from which all minimal explanations can be retrieved. We develop a tractable method (in data complexity) for computing all representative explanations in a consistent ontology. Experimental results demonstrate that the method is efficient and scalable for ontologies with large ABoxes.; ABox abduction is an important reasoning mechanism for description logic ontologies. It computes all minimal explanations (sets of ABox assertions) whose appending to a consistent ontology enforces the entailment of an observation while keeps the ontology consistent. We focus on practical computation for a general problem of ABox abduction, called the query abduction problem, where an observation is a Boolean conjunctive query and the explanations may contain fresh individuals neither in the ontology nor in the observation. However, in this problem there can be infinitely many minimal explanations. Hence we first identify a class of TBoxes called first-order rewritable TBoxes. It guaran-tees the existence of finitely many minimal explanations and is sufficient for many ontology applications. To reduce the number of explanations that need to be computed, we introduce a special kind of minimal explanations called representative explanations from which all minimal explanations can be retrieved. We develop a tractable method (in data complexity) for computing all representative explanations in a consistent ontology. Experimental results demonstrate that the method is efficient and scalable for ontologies with large ABoxes.
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/16600
Collection中国科学院软件研究所
Corresponding AuthorDu, Jianfeng
Recommended Citation
GB/T 7714
Du, Jianfeng ,Wang, Kewen ,Shen, Yi-Dong ,et al. A tractable approach to ABox abduction over description logic ontologies[C]. AI Access Foundation,2014:1034-1040.
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