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Stream reasoning in temporal datalog

Abstract:

In recent years, there has been an increasing interest in extending traditional stream processing engines with logical, rule-based, reasoning capabilities. This poses significant theoretical and practical challenges since rules can derive new information and propagate it both towards past and future time points; as a result, streamed query answers can depend on data that has not yet been received, as well as on data that arrived far in the past. Stream reasoning algorithms, however, must be a...

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Publication status:
Published
Peer review status:
Peer reviewed

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  • (Accepted manuscript, pdf, 307.5KB)

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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 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 Division
Department:
Computer Science
Role:
Author
Sirius Center for Scalable Data Access in the Oil and Gas Domain More from this funder
Royal Society More from this funder
Publisher:
AAAI Press Publisher's website
Journal:
32nd AAAI Conference on Artificial Intelligence (AAAI'18) Journal website
Pages:
1941-1948
Host title:
32nd AAAI Conference on Artificial Intelligence (AAAI'18)
Publication date:
2018-04-25
Acceptance date:
2017-11-08
ISSN:
2159-5399
Source identifiers:
745827
Keywords:
Pubs id:
pubs:745827
UUID:
uuid:436878bf-2d51-4177-bf28-d11672ef46a9
Local pid:
pubs:745827
Deposit date:
2017-11-15

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