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A Meta-reasoner to Rule Them All: Automated Selection of OWL Reasoners Based on Efficiency

Published: 03 November 2014 Publication History

Abstract

It has been shown, both theoretically and empirically, that reasoning about large and expressive ontologies is computationally hard. Moreover, due to the different reasoning algorithms and optimisation techniques employed, each reasoner may be efficient for ontologies with different characteristics. Based on recently-developed prediction models for various reasoners for reasoning performance, we present our work in developing a meta-reasoner that automatically selects from a number of state-of-the-art OWL reasoners to achieve optimal efficiency. Our preliminary evaluation shows that the meta-reasoner significantly and consistently outperforms 6 state-of-the-art reasoners and it achieves a performance close to the hypothetical gold standard reasoner.

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  • (2021)Adaptability in biology classroom: A metacognitive discourseTHE 4TH INTERNATIONAL CONFERENCE ON MATHEMATICS AND SCIENCE EDUCATION (ICoMSE) 2020: Innovative Research in Science and Mathematics Education in The Disruptive Era10.1063/5.0043258(030015)Online publication date: 2021
  • (2015)RO: An Efficient Ranking-Based Reasoner for OWL OntologiesThe Semantic Web - ISWC 201510.1007/978-3-319-25007-6_19(322-338)Online publication date: 11-Oct-2015

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  1. A Meta-reasoner to Rule Them All: Automated Selection of OWL Reasoners Based on Efficiency

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      cover image ACM Conferences
      CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management
      November 2014
      2152 pages
      ISBN:9781450325981
      DOI:10.1145/2661829
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 03 November 2014

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      Author Tags

      1. meta-reasoner
      2. ontology
      3. owl reasoner
      4. prediction models
      5. the sematic web

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      • (2021)Adaptability in biology classroom: A metacognitive discourseTHE 4TH INTERNATIONAL CONFERENCE ON MATHEMATICS AND SCIENCE EDUCATION (ICoMSE) 2020: Innovative Research in Science and Mathematics Education in The Disruptive Era10.1063/5.0043258(030015)Online publication date: 2021
      • (2015)RO: An Efficient Ranking-Based Reasoner for OWL OntologiesThe Semantic Web - ISWC 201510.1007/978-3-319-25007-6_19(322-338)Online publication date: 11-Oct-2015

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