Is a Voting Approach Accurate for Opinion Mining?

Michel Plantié 1 Mathieu Roche 2 Gérard Dray 1 Pascal Poncelet 3
2 TEXTE - Exploration et exploitation de données textuelles
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
3 TATOO - Fouille de données environnementales
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : In this paper, we focus on classifying documents according to opinion and value judgment they contain. The main originality of our approach is to combine lin- guistic pre-processing, classification and a voting system using several classification methods. In this context, the relevant representation of the documents allows to determine the features for storing textual data in data warehouses. The conducted experiments on very large corpora from a French challenge on text mining (DEFT) show the efficiency of our approach.
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Michel Plantié, Mathieu Roche, Gérard Dray, Pascal Poncelet. Is a Voting Approach Accurate for Opinion Mining?. DaWaK: Data Warehousing and Knowledge Discovery, Sep 2008, Torino, Italy. pp.413-422, ⟨10.1007/978-3-540-85836-2_39⟩. ⟨hal-00353944⟩

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