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Modelisation de l'incertitude et de l'imprecision de donnees de crowdsourcing : MONITOR

Abstract : Crowdsourcing is defined as the outsourcing of tasks to a crowd of contributors. The crowd is very diverse on these platforms and includes malicious contributors attracted by the remuneration of tasks and not conscientiously performing them. It is essential to identify these contributors in order to avoid considering their responses. As not all contributors have the same aptitude for a task, it seems appropriate to give weight to their answers according to their qualifications. This paper, published at the ICTAI 2019 conference, proposes a method, MONITOR, for estimating the profile of the contributor and aggregating the responses using belief function theory.
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https://hal.inria.fr/hal-02487535
Contributor : Constance Thierry <>
Submitted on : Tuesday, February 25, 2020 - 5:40:19 PM
Last modification on : Friday, October 23, 2020 - 4:52:04 PM
Long-term archiving on: : Tuesday, May 26, 2020 - 12:20:39 PM

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  • HAL Id : hal-02487535, version 1
  • ARXIV : 2002.11717

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Constance Thierry, Jean-Christophe Dubois, Yolande Le Gall, Arnaud Martin. Modelisation de l'incertitude et de l'imprecision de donnees de crowdsourcing : MONITOR. Extraction et Gestion des Connaissances (EGC), Jan 2020, Bruxelles, Belgique. ⟨hal-02487535⟩

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