Closed-world concept induction for learning in OWL knowledge bases

David Ratcliffe*, Kerry Taylor

*Corresponding author for this work

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

    6 Citations (Scopus)

    Abstract

    We present a general-purpose method for inducing OWL class descriptions over data and knowledge captured with RDF and OWL in a closed-world way. We combine our approach with a top-down refinement-based search with Description Logic (DL) expressions which incorporates OWL background knowledge. Our methods are designed for speed and scalability to support analysis tasks like data mining over large knowledge-rich data sets. We compare our methods to a state-of the-art DL learning tool with respect to a large benchmark problem to demonstrate the speed and effectiveness of our approach.

    Original languageEnglish
    Title of host publicationKnowledge Engineering and Knowledge Management - 19th International Conference, EKAW 2014, Proceedings
    EditorsKrzysztof Janowicz, Stefan Schlobach, Patrick Lambrix, Eero Hyvönen
    PublisherSpringer Verlag
    Pages429-440
    Number of pages12
    ISBN (Electronic)9783319137032
    DOIs
    Publication statusPublished - 2014
    Event19th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2014 - Linköping, Sweden
    Duration: 24 Nov 201428 Nov 2014

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume8876
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference19th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2014
    Country/TerritorySweden
    CityLinköping
    Period24/11/1428/11/14

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