Converting instance checking to subsumption: A rethink for object queries over practical ontologies

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Instance checking is considered a central service for data retrieval from description logic (DL) ontologies. In this paper, we propose a revised most specific concept (MSC) method for DL SHI, which converts instance checking into subsumption problems. This revised method can generate small concepts that are specific-enough to answer a given query, and allow reasoning to explore only a subset of the ABox data to achieve efficiency. Experiments show effectiveness of our proposed method in terms of concept size reduction and the improvement in reasoning efficiency.

Original languageEnglish (US)
Title of host publicationProceedings of the National Conference on Artificial Intelligence
PublisherAI Access Foundation
Pages3142-3143
Number of pages2
ISBN (Electronic)9781577356806
StatePublished - Jan 1 2014
Event28th 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 - Quebec City, Canada
Duration: Jul 27 2014Jul 31 2014

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume4

Other

Other28th 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
CountryCanada
CityQuebec City
Period7/27/147/31/14

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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  • Cite this

    Xu, J., Visser, U., & Kabuka, M. (2014). Converting instance checking to subsumption: A rethink for object queries over practical ontologies. In Proceedings of the National Conference on Artificial Intelligence (pp. 3142-3143). (Proceedings of the National Conference on Artificial Intelligence; Vol. 4). AI Access Foundation.