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Master Thesis

TALN, Text-Mining et ontologie pour la maintenance de panneaux photovoltaïques

Abstract : The very large amount of circulating data, around the world is related to the rise of the digital. Many questions stand out as to the uses that can be made of these data. As a resort EDF aims to launch research projects to make use of the data at his disposal. Among these projects, one looks at textual data. The analysis conducted in this thesis was established as part of this project. The aim is to use textual data and extract information to optimize the maintenance process in photovoltaic parks. The issue is: How can natural language processing optimize the process of designing, operating and maintaining photovoltaic systems? To answer this, several actions have been carried out in order to adapt a textual analysis application to the solar domain. The application lays on an on an ontology and rules. The main actions described in this thesis are intended to format the initial data in order to extend the ontology, so that the application is compatible with the processing of textual data, from maintenance reports of solar panels.
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Master Thesis
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https://dumas.ccsd.cnrs.fr/dumas-02322096
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Submitted on : Monday, October 21, 2019 - 3:33:07 PM
Last modification on : Friday, November 6, 2020 - 4:18:53 AM
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  • HAL Id : dumas-02322096, version 1

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Sami Bouhouche. TALN, Text-Mining et ontologie pour la maintenance de panneaux photovoltaïques. Sciences de l'Homme et Société. 2019. ⟨dumas-02322096⟩

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