research-article

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

Authors:

Valentina Beretta,

Sébastien Harispe,

Isabelle MougenotAuthors Info & Claims

WIMS '16: Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics

Article No.: 15, Pages 1 - 12

https://doi.org/10.1145/2912845.2912848

Published: 13 June 2016 Publication History

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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Cited By

Pradhan RAref WPrabhakar S(2018)Leveraging Data Relationships to Resolve Conflicts from Disparate Data SourcesDatabase and Expert Systems Applications10.1007/978-3-319-98812-2_7(99-115)Online publication date: 3-Sep-2018
https://dl.acm.org/doi/10.1007/978-3-319-98812-2_7
Beretta VHarispe SRanwez SMougenot I(2018)Combining Truth Discovery and RDF Knowledge Bases to Their Mutual AdvantageThe Semantic Web – ISWC 201810.1007/978-3-030-00671-6_38(652-668)Online publication date: 8-Oct-2018
https://dl.acm.org/doi/10.1007/978-3-030-00671-6_38

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cover image ACM Other conferences

WIMS '16: Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics

June 2016

309 pages

ISBN:9781450340564

DOI:10.1145/2912845

Copyright © 2016 ACM.

© 2016 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Association for Computing Machinery

New York, NY, United States

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Published: 13 June 2016

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WIMS '16

WIMS '16: International Conference on Web Intelligence, Mining and Semantics

June 13 - 15, 2016

Nîmes, France

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WIMS '16 Paper Acceptance Rate 36 of 53 submissions, 68%;

Overall Acceptance Rate 140 of 278 submissions, 50%

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Cited By

Pradhan RAref WPrabhakar S(2018)Leveraging Data Relationships to Resolve Conflicts from Disparate Data SourcesDatabase and Expert Systems Applications10.1007/978-3-319-98812-2_7(99-115)Online publication date: 3-Sep-2018
https://dl.acm.org/doi/10.1007/978-3-319-98812-2_7
Beretta VHarispe SRanwez SMougenot I(2018)Combining Truth Discovery and RDF Knowledge Bases to Their Mutual AdvantageThe Semantic Web – ISWC 201810.1007/978-3-030-00671-6_38(652-668)Online publication date: 8-Oct-2018
https://dl.acm.org/doi/10.1007/978-3-030-00671-6_38

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