ArThUR: A Tool for Markov Logic Network

Axel Bodart, Keyvin Evrard, James Jerson Ortiz Vega, Pierre Yves Schobbens

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Résumé

Logical approaches-and ontologies in particular-offer a welladapted framework for representing knowledge present on the Semantic Web (SW). These ontologies are formulated in Web Ontology Language (OWL2), which are based on expressive Description Logics (DL). DL are a subset of First-Order Logic (FOL) that provides decidable reasoning. Based on DL, it is possible to rely on inference mechanisms to obtain new knowledge from axioms, rules and facts specified in the ontologies. However, these classical inference mechanisms do not deal with : uncertainty probabilities. Several works recently targeted those issues (i.e. Pronto, PR-OWL, BayesOWL, etc.), but none of them combines OWL2 with Markov Logic Networks (MLN) formalism. Several open source software packages for MLN are available (e.g. Alchemy, Tuffy, RockIt, etc.). In this paper, we present ArThUR, a Java framework for reasoning with probabilistic information in the SW. ArThUR incorporate three open source software packages for MLN, which is able to reason with uncertainty information, showing that it can be used in several real-world domains. We also show several experiments of our tool with different ontologies.

langue originaleAnglais
titreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditeurSpringer Verlag
Pages319-328
Nombre de pages10
Volume8842
ISBN (imprimé)9783662455494
étatPublié - 2014
EvénementInternational Workshops: OTM Academy,OTM Industry Case Studies Program, C and TC, EI2N, INBAST, ISDE, META4eS, MSC, and OnToContent 2014 - Amantea, Italie
Durée: 27 oct. 201431 oct. 2014

Série de publications

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8842
ISSN (imprimé)03029743
ISSN (Electronique)16113349

Une conférence

Une conférenceInternational Workshops: OTM Academy,OTM Industry Case Studies Program, C and TC, EI2N, INBAST, ISDE, META4eS, MSC, and OnToContent 2014
PaysItalie
La villeAmantea
période27/10/1431/10/14

Empreinte digitale

Ontology
Logic
Description Logics
Open Source Software
Semantic Web
Software Package
Software packages
Reasoning
Uncertainty
First-order Logic
Axioms
Java
Subset
Experiment
Experiments
Framework
Knowledge
Open source software

Citer ceci

Bodart, A., Evrard, K., Ortiz Vega, J. J., & Schobbens, P. Y. (2014). ArThUR: A Tool for Markov Logic Network. Dans Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol 8842, p. 319-328). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol 8842). Springer Verlag.
Bodart, Axel ; Evrard, Keyvin ; Ortiz Vega, James Jerson ; Schobbens, Pierre Yves. / ArThUR: A Tool for Markov Logic Network. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 8842 Springer Verlag, 2014. p. 319-328 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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abstract = "Logical approaches-and ontologies in particular-offer a welladapted framework for representing knowledge present on the Semantic Web (SW). These ontologies are formulated in Web Ontology Language (OWL2), which are based on expressive Description Logics (DL). DL are a subset of First-Order Logic (FOL) that provides decidable reasoning. Based on DL, it is possible to rely on inference mechanisms to obtain new knowledge from axioms, rules and facts specified in the ontologies. However, these classical inference mechanisms do not deal with : uncertainty probabilities. Several works recently targeted those issues (i.e. Pronto, PR-OWL, BayesOWL, etc.), but none of them combines OWL2 with Markov Logic Networks (MLN) formalism. Several open source software packages for MLN are available (e.g. Alchemy, Tuffy, RockIt, etc.). In this paper, we present ArThUR, a Java framework for reasoning with probabilistic information in the SW. ArThUR incorporate three open source software packages for MLN, which is able to reason with uncertainty information, showing that it can be used in several real-world domains. We also show several experiments of our tool with different ontologies.",
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Bodart, A, Evrard, K, Ortiz Vega, JJ & Schobbens, PY 2014, ArThUR: A Tool for Markov Logic Network. Dans Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). VOL. 8842, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), VOL. 8842, Springer Verlag, p. 319-328, International Workshops: OTM Academy,OTM Industry Case Studies Program, C and TC, EI2N, INBAST, ISDE, META4eS, MSC, and OnToContent 2014, Amantea, Italie, 27/10/14.

ArThUR: A Tool for Markov Logic Network. / Bodart, Axel; Evrard, Keyvin; Ortiz Vega, James Jerson; Schobbens, Pierre Yves.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 8842 Springer Verlag, 2014. p. 319-328 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol 8842).

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférenceArticle dans les actes d'une conférence/un colloque

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Bodart A, Evrard K, Ortiz Vega JJ, Schobbens PY. ArThUR: A Tool for Markov Logic Network. Dans Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 8842. Springer Verlag. 2014. p. 319-328. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).