- Abstract:
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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...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Accepted Manuscript
- Files:
-
-
(pdf, 531.1KB)
-
- Publisher copy:
- 10.1007/978-3-030-00338-8_3
-
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- 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
- Copyright holder:
- Springer Nature Switzerland
- Copyright date:
- 2018
- Notes:
- © Springer Nature Switzerland AG 2018. This is the accepted manuscript version of the article. The final version is available online from Springer Verlag at: https://doi.org/10.1007/978-3-030-00338-8_3
Conference item
A tutorial on query answering and reasoning over probabilistic knowledge bases
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