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MV-Datalog+-: Effective rule-based reasoning with uncertain observations

Abstract:

Modern applications combine information from a great variety of sources. Oftentimes, some of these sources, like machine-learning systems, are not strictly binary but associated with some degree of (lack of) confidence in the observation. We propose MV-Datalog and as extensions of Datalog and, respectively, to the fuzzy semantics of infinite-valued Łukasiewicz logic as languages for effectively reasoning in scenarios where such uncertain observations occur. We show that the semantics of...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1017/S1471068422000199

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
ORCID:
0000-0002-7601-3727
Publisher:
Cambridge University Press Publisher's website
Journal:
Theory and Practice of Logic Programming Journal website
Volume:
22
Issue:
5
Pages:
678-692
Publication date:
2022-07-26
Acceptance date:
2022-07-01
DOI:
EISSN:
1475-3081
ISSN:
1471-0684
Language:
English
Keywords:
Pubs id:
1273700
Local pid:
pubs:1273700
Deposit date:
2022-09-18

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