Classifying texts through natural language parsing and semantic filtering - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Accéder directement au contenu
Communication Dans Un Congrès Année : 2007

Classifying texts through natural language parsing and semantic filtering

Résumé

This paper presents a study in text classification through semantic and syntactic natural language processing. The authors have used a parser for French, SYGFRAN, and applied it to a real project of press articles classification. The results of this research on a corpus of 4, 843 texts containing more than 76, 000 sentences are described. Classification into 37 categories has been obtained through meaning discrimination by semantic filtering techniques, explained in the document.
Fichier principal
Vignette du fichier
JCVPLTC.pdf (96.06 Ko) Télécharger le fichier

Dates et versions

lirmm-00178563 , version 1 (11-10-2007)

Identifiants

  • HAL Id : lirmm-00178563 , version 1

Citer

Jacques Chauché, Violaine Prince. Classifying texts through natural language parsing and semantic filtering. 3rd International Language and Technology Conference, Oct 2007, Poznan, Pologne, pp.012-020. ⟨lirmm-00178563⟩
109 Consultations
285 Téléchargements

Partager

Gmail Facebook X LinkedIn More