A meta-reasoner to rule them all: Automated selection of OWL reasoners based on efficiency

Yong-Bin Kang, Shonali Krishnaswamy, Yuan-Fang Li

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    3 Citations (Scopus)

    Abstract

    It has been shown, both theoretically and empirically, that 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 effciency. Our preliminary evaluation shows that the meta-reasoner signicantly and consistently outperforms 6 state-of-the-art reasoners and it achieves a performance close to the hypothetical gold standard reasoner.
    reasoning about large and expressive ontologies is computationally
    hard. Moreover, due to the dierent reasoning algorithms
    and optimisation techniques employed, each reasoner
    may be ecient for ontologies with dierent 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
    eciency. Our preliminary evaluation shows that the
    meta-reasoner signicantly and consistently outperforms 6
    state-of-the-art reasoners and it achieves a performance close
    to the hypothetical gold standard reasoner.
    Original languageEnglish
    Title of host publicationProceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM'14)
    EditorsMinos Garofalakis, Ian Soboroff, Torsten Suel, Min Wang
    Place of PublicationNew York NY USA
    PublisherAssociation for Computing Machinery (ACM)
    Pages1935-1938
    Number of pages4
    ISBN (Print)9781450325981
    DOIs
    Publication statusPublished - 2014
    EventACM International Conference on Information and Knowledge Management 2014 - Shanghai, China
    Duration: 3 Nov 20147 Nov 2014
    Conference number: 23rd
    https://dl.acm.org/doi/proceedings/10.1145/2661829

    Conference

    ConferenceACM International Conference on Information and Knowledge Management 2014
    Abbreviated titleCIKM 2014
    CountryChina
    CityShanghai
    Period3/11/147/11/14
    Internet address

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