On the Explanation of SameAs Statements using Argumentation

Abdallah Arioua 1, 2 Madalina Croitoru 2 Laura Papaleo 3 Nathalie Pernelle 3 Swan Rocher 2
1 IATE - Ingénierie des Agro-polymères et Technologies Émergentes
2 GRAPHIK - Graphs for Inferences on Knowledge
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
3 LRI - Laboratoire de Recherche en Informatique
Abstract : Due to the impressive growing of the LOD graph in the last years, assuring the quality of its content is becoming a very important issue. Thus, it is crucial to design techniques for supporting experts in validating facts and links in complex data sources. Here, we focus on identity links (sameAs) and apply argumentation semantics to (i) detect inconsistencies in sameAs statements and to (ii) explain them to the experts using dialogues. We formalize the framework, explaining its purposes. Finally we provide a promising preliminary evaluation and discuss on some interesting future directions we foresee.
Type de document :
Communication dans un congrès
SUM: Scalable Uncertainty Management, Sep 2016, Nice, France. 10th International Conference on Scalable Uncertainty Management, LNCS (9858), pp.51-66, 2016, 〈http://sum2016.unice.fr〉. 〈10.1007/978-3-319-45856-4_4〉
Liste complète des métadonnées
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01337012
Contributeur : Abdallah Arioua <>
Soumis le : vendredi 24 juin 2016 - 12:23:02
Dernière modification le : jeudi 5 avril 2018 - 12:30:09

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LIRMM | INRA | UMR8623 | INRIA | GRAPHIK | CIRAD | CENTRALESUPELEC | UNIV-PARIS-SACLAY | LRI-LAHDAK | MIPS | BA | UNIV-MONTPELLIER

Citation

Abdallah Arioua, Madalina Croitoru, Laura Papaleo, Nathalie Pernelle, Swan Rocher. On the Explanation of SameAs Statements using Argumentation. SUM: Scalable Uncertainty Management, Sep 2016, Nice, France. 10th International Conference on Scalable Uncertainty Management, LNCS (9858), pp.51-66, 2016, 〈http://sum2016.unice.fr〉. 〈10.1007/978-3-319-45856-4_4〉. 〈lirmm-01337012〉

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