Cited by 8Semantic Web and OntologiesMobile Crowdsensing and CrowdsourcingData Quality and Management

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How Can Ontologies Give You Clue for Truth-Discovery? An Exploratory Study

Beretta, Valentina, Harispe, Sébastien, Ranwez, Sylvie, Mougenot, Isabelle·2016·Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics

Abstract

The main aim of truth-finding methods is to identify the most reliable and trustworthy data among a set of facts. Since existing methods assume a single true value, they cannot deal with numerous real-world use cases in which a set of true values exists for a given fact, even for functional predicate (e.g. Picasso is born in Màlaga and in Spain). This paper studies how traditional truth-finding methods can be adapted to this setting. After introducing a new definition of true value and discussing associated implications, we propose an approach that can be used to identify true values among a set of non-conflicting claims; it takes advantage of belief functions to incorporate knowledge about value relationships in the form of a partial ordering of claimed values. By reducing the error rate up to 30% adapting classical approaches, the effectiveness and suitability of our proposal is clearly highlighted through empirical experiments performed on DBpedia.

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Crossref · 10.1145/2912845.2912848

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Research works printed but not linked: 31

  1. S. Auer , C. Bizer , G. Kobilarov , J. Lehmann , R. Cyganiak , and Z. Ives . The Semantic Web: 6th International Semantic Web Conference , 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007 , Busan, Korea, November 11-15, 2007. Proceedings, chapter DBpedia: A Nucleus for a Web of Open Data, pages 722 -- 735 . Springer Berlin Heidelberg , Berlin, Heidelberg, 2007. S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak, and Z. Ives. The Semantic Web: 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007. Proceedings, chapter DBpedia: A Nucleus for a Web of Open Data, pages 722--735. Springer Berlin Heidelberg, Berlin, Heidelberg, 2007.
  2. L. Berti-Equille , A. D. Sarma , Xin, Dong, A. Marian , and D. Srivastava . Sailing the Information Ocean with Awareness of Currents: Discovery and Application of Source Dependence . Cidr , 2009 . L. Berti-Equille, A. D. Sarma, Xin, Dong, A. Marian, and D. Srivastava. Sailing the Information Ocean with Awareness of Currents: Discovery and Application of Source Dependence. Cidr, 2009.
  3. 10.5555/1883784.1883795 · DOI
  4. S. Brin and L. Page . The Anatomy of a Search Engine . Proceedings of the 7th International World-Wide Web Conference , page 20 , 1998 . S. Brin and L. Page. The Anatomy of a Search Engine. Proceedings of the 7th International World-Wide Web Conference, page 20, 1998.
  5. 10.14778/1920841.1921008 · DOI
  6. 10.14778/1687627.1687690 · DOI · Paper page
  7. 10.14778/1687627.1687691 · DOI · Paper page
  8. 10.14778/2777598.2777603 · DOI · Paper page
  9. 10.1145/302979.303001 · DOI
  10. 10.1145/1718487.1718504 · DOI
  11. 10.1016/j.websem.2007.09.005 · DOI
  12. 10.1145/1963192.1963220 · DOI
  13. 10.1109/FUZZ-IEEE.2015.7337964 · DOI
  14. 10.1093/bioinformatics/btt581 · DOI
  15. 10.2200/S00639ED1V01Y201504HLT027 · DOI
  16. 10.1002/asi.v59:3 · DOI
  17. 10.1145/324133.324140 · DOI
  18. Y. Li , J. Gao , C. Meng , Q. Li , L. Su , B. Zhao , W. Fan , and J. Han . A survey on truth discovery. CoRR, abs/1505.02463 , 2015 . Y. Li, J. Gao, C. Meng, Q. Li, L. Su, B. Zhao, W. Fan, and J. Han. A survey on truth discovery. CoRR, abs/1505.02463, 2015. · arXiv
  19. D. Lin . An information-theoretic definition of similarity . In 15th International Conference of Machine Learning (ICML 1998 ), volume 98 , pages 296 -- 304 , 1998 . D. Lin. An information-theoretic definition of similarity. In 15th International Conference of Machine Learning (ICML 1998), volume 98, pages 296--304, 1998.
  20. 10.5555/1873781.1873880 · DOI
  21. 10.5555/2283696.2283785 · DOI
  22. 10.1145/2588555.2593674 · DOI
  23. 10.1145/2488388.2488479 · DOI
  24. 10.1016/j.jbi.2011.03.013 · DOI
  25. G. Shafer A mathematical theory of evidence , volume 1 . Princeton university press Princeton , 1976 . G. Shafer et al. A mathematical theory of evidence, volume 1. Princeton university press Princeton, 1976. · DOI
  26. D. A. Waguih and L. Berti-Equille . Truth discovery algorithms: An experimental evaluation. CoRR, abs/1409.6428 , 2014 . D. A. Waguih and L. Berti-Equille. Truth discovery algorithms: An experimental evaluation. CoRR, abs/1409.6428, 2014. · arXiv
  27. 10.1109/ICDCS.2013.54 · DOI
  28. 10.1145/2185677.2185737 · DOI
  29. 10.1145/2806416.2806443 · DOI
  30. 10.1109/TKDE.2007.190745 · DOI
  31. 10.14778/2168651.2168656 · DOI

Metadata

Authors
Beretta, V., Harispe, S., Ranwez, S., & Mougenot, I.
Affiliations
  • IMT Mines Alès (FR)
  • Université de Montpellier (FR)
Venue
Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics
Publisher
ACM
Published
2016-06-13
Pages
1-12
OpenAlex
W2497433576
Cited by
8
References
0
Citations by year
2024: 1 · 2022: 1 · 2019: 1 · 2018: 4 · 2017: 1
FWCI
1.08
Type
conference paper
Language
en
Open access
closed
Locations
  • International Conference on Web Intelligence, Mining and Semantics (publishedVersion)
  • HAL (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
  • Physical Sciences › Computer Science › Computer Science Applications › Mobile Crowdsensing and Crowdsourcing
  • Physical Sciences › Computer Science › Information Systems › Data Quality and Management
Keywords
truth discovery, ontology (information science), belief functions, DBpedia, knowledge base quality

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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