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A tutorial on query answering and reasoning over probabilistic knowledge bases

Abstract:

Large-scale probabilistic knowledge bases are becoming increasingly important in academia and industry alike. They are constantly extended with new data, powered by modern information extraction tools that associate probabilities with knowledge base facts. This tutorial is dedicated to give an understanding of various query answering and reasoning tasks that can be used to exploit the full potential of probabilistic knowledge bases. In the first part of the tutorial, we focus on (tuple-indepe...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

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Publisher copy:
10.1007/978-3-030-00338-8_3

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Oxford college:
Hertford College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author
ORCID:
0000-0002-7644-1668
Publisher:
Springer Verlag Publisher's website
Volume:
11078
Pages:
35-77
Series:
Lecture Notes in Computer Science
Publication date:
2018-09-22
Acceptance date:
2018-07-28
DOI:
ISSN:
0302-9743
Pubs id:
pubs:922425
URN:
uri:13cae303-2ea6-4c3c-8e28-570924116ea6
UUID:
uuid:13cae303-2ea6-4c3c-8e28-570924116ea6
Local pid:
pubs:922425
ISBN:
9783030003371

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