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Optimised maintenance of datalog materialisations

Abstract:

To efficiently answer queries, datalog systems often materialise all consequences of a datalog program, so the materialisation must be updated whenever the input facts change. Several solutions to the materialisation update problem have been proposed. The Delete/Rederive (DRed) and the Backward/ Forward (B/F) algorithms solve this problem for general datalog, but both contain steps that evaluate rules ‘backwards’ by matching their heads to a fact and evaluating the partially instantiated rule...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Oxford college:
Oriel College
Role:
Author
ORCID:
0000-0002-2685-7462
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Name:
Engineering and Physical Sciences Research Council
Grant:
ED3
Publisher:
Association for the Advancement of Artificial Intelligence
Host title:
Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)
Journal:
Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) More from this journal
Publication date:
2018-04-25
Acceptance date:
2017-11-09
Pubs id:
pubs:847669
UUID:
uuid:c9678881-07bd-4974-9ac4-f142598719b4
Local pid:
pubs:847669
Source identifiers:
847669
Deposit date:
2018-09-25

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