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Master Thesis

Adaptation des techniques de Text Mining aux données conversationnelles issues de l'oral

Abstract : This thesis tackles the problem of processing data derived from the oral. Indeed, businesses are full of data about their customers, data from satisfaction surveys, forums, call-center... Which are not workable. First, a reminder of existing work on the linguistic analysis of data from the spontaneous speech is proposed (see p. 75 à 80). The manual and automatic transcriptions of speech features from telephone conversations between agents and customers EDF are analyzed (see p. 75 à 80). Finally a solution is proposed to accommodate a Skill Cartridge to specific data (see p. 75).
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Master Thesis
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https://dumas.ccsd.cnrs.fr/dumas-00567888
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Submitted on : Tuesday, February 22, 2011 - 10:21:35 AM
Last modification on : Sunday, March 14, 2021 - 9:54:03 PM
Long-term archiving on: : Monday, May 23, 2011 - 2:55:49 AM

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  • HAL Id : dumas-00567888, version 1

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Charlotte Danesi. Adaptation des techniques de Text Mining aux données conversationnelles issues de l'oral. Linguistique. 2010. ⟨dumas-00567888⟩

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