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Ontology module extraction via datalog reasoning

Abstract:

Module extraction — the task of computing a (preferably small) fragment M of an ontology T that preserves entailments over a signature S — has found many applications in recent years. Extracting modules of minimal size is, however, computationally hard, and often algorithmically infeasible. Thus, practical techniques are based on approximations, where M provably captures the relevant entailments, but is not guaranteed to be minimal. Existing approximations, however, ensure that M preserves...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author

Contributors

Role:
Editor
Role:
Editor
Engineering and Physical Sciences Research Council More from this funder
Royal Society More from this funder
European Union More from this funder
Publisher:
AAAI Press Publisher's website
Pages:
1410-1416
Host title:
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence and the Twenty-Seventh Innovative Applications of Artificial Intelligence Conference, January 25–30, 2015, Austin, Texas, USA
Publication date:
2015-01-01
EISSN:
2374-3468
ISSN:
2159-5399
Source identifiers:
577295
ISBN:
9781577356981
Keywords:
Pubs id:
pubs:577295
UUID:
uuid:66582e16-9d83-42fc-96a9-3d662c6b62d6
Local pid:
pubs:577295
Deposit date:
2016-03-06

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