Une Approche Mixte -statistique et structurelle- pour le Résumé Automatique
| Autor: | Bossard, Aurélien |
|---|---|
| Přispěvatelé: | Bossard, Aurélien, Laboratoire d'Informatique de Paris-Nord (LIPN), Université Sorbonne Paris Cité (USPC)-Institut Galilée-Université Paris 13 (UP13)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | francouzština |
| Rok vydání: | 2009 |
| Předmět: |
[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing
[SCCO.COMP] Cognitive science/Computer science Résumé automatique Analyse discursive [SCCO.COMP]Cognitive science/Computer science [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing [SHS.LANGUE]Humanities and Social Sciences/Linguistics [SCCO.LING]Cognitive science/Linguistics Traitement automatique du langage [SCCO.LING] Cognitive science/Linguistics [SHS.LANGUE] Humanities and Social Sciences/Linguistics Extraction d'information |
| Zdroj: | Actes de TALN 2009 Traitement Automatique du Langage Naturel Traitement Automatique du Langage Naturel, Jun 2009, Senlis, France. pp.01-10 |
| Popis: | International audience; Automatic multi-document summarization techniques have recently evolved into statistical methods for selecting the sentences that will be used to generate the summary. In this paper, we present a system in accordance with « State-of-the-art » — CBSEAS — that we have developped for the « Opinion Task » (automatic summaries of opinions from blogs) and the « Update Task » (automatic summaries of newswire articles and information update) of the TAC 2008 evaluation campaign, and show the interest of structural and linguistic analysis of the documents to summarize. We also present our study on news structure and its integration to CBSEAS impact. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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