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Communication dans un congrès

Generic and massively concurrent computation of belief combination rules – a MapReduce approach

Abdelmalek Toumi 1, 2 Frédéric Dambreville 1, 3
1 Pôle STIC_REMS
ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne
2 Lab-STICC_ENSTAB_CID_TOMS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
3 Lab-STICC_ENSTAB_CID_SFIIS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : This paper presents a generic and versatile approach for implementing combining rules on preprocessed belief functions, issuing from a large population of information sources. In this paper, we address two issues, which are the intrinsic complexity of the rules processing, and the possible large amount of requested combinations. We present a fully distributed approach, based on a MapReduce scheme. This approach is generic. In particular, we compare two implementations of three sources Dubois & Prade rule within framework Apache Spark and Apache Flink.
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https://hal.archives-ouvertes.fr/hal-01653416
Contributeur : Annick Billon-Coat <>
Soumis le : vendredi 1 décembre 2017 - 14:20:20
Dernière modification le : mercredi 24 juin 2020 - 16:19:51

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Abdelmalek Toumi, Frédéric Dambreville. Generic and massively concurrent computation of belief combination rules – a MapReduce approach. BDAW'16, Nov 2016, Blagoevgrad, Bulgaria. ⟨10.1145/3010089.3010136⟩. ⟨hal-01653416⟩

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