Lexical and Semantic Methods in Inner Text Topic Segmentation: A Comparison between C99 and Transeg

Alexandre Labadié; Violaine Prince

doi:10.1007/978-3-540-69858-6_40

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Lexical and Semantic Methods in Inner Text Topic Segmentation: A Comparison between C99 and Transeg

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Lexical and Semantic Methods in Inner Text Topic Segmentation: A Comparison between C99 and Transeg

Alexandre Labadié et Violaine Prince

13th International Conference on Applications of Natural Language to Information Systems, Vol.LNCS(5039), pp.347-349

NLDB: Natural Language Processing and Information Systems (London, United Kingdom, 24/06/2008–27/06/2008)

24/06/2008

DOI: https://doi.org/10.1007/978-3-540-69858-6_40

Résumé

This paper present a semantic and syntactic distance based method in topic text segmentation and compare it to a very well known text segmentation algorithm: c99. To do so we ran the two algorithms on a corpus of twenty two French political discourses and compared their results.

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Titre: Lexical and Semantic Methods in Inner Text Topic Segmentation: A Comparison between C99 and Transeg
Créateurs - sans rôle: Alexandre Labadié - Université de Montpellier, Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier - LIRMM
Violaine Prince - Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier
Détails de publication: 13th International Conference on Applications of Natural Language to Information Systems, Vol.LNCS(5039), pp.347-349
Colloque: NLDB: Natural Language Processing and Information Systems (London, United Kingdom, 24/06/2008–27/06/2008)
Identifiants: 9945367109311
Unité académique: Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier - LIRMM
Langue: English
Type de ressource: Conference proceeding
Champs locaux: lirmm-00336162