Por favor, use este identificador para citar o enlazar este ítem: http://repositoriodigital.ipn.mx/handle/123456789/16621
Título : Detecting Salient Events in Large Corpora by a Combination of NLP and Data Mining Techniques
Otros títulos : Detección de destacados eventos en un corpus grande combinando técnicas para PLN y minería de datos
Autor : Battistelli, Delphine
Charnois, Thierry
Luc Minel, Jean
Teissèdre, Charles
Palabras clave : Keywords. Dates, temporal adverbials, event extraction, sequential pattern.
Fecha de publicación : 7-jun-2013
Editorial : Revista Computación y Sistemas; Vol. 17 No.2
Citación : Revista Computación y Sistemas; Vol. 17 No.2
Citación : Revista Computación y Sistemas;Vol. 17 No.2
Resumen : Abstract. In this paper, we present a framework and a system that extracts “salient” events relevant to a query from a large collection of documents, and which also enables events to be placed along a timeline. Each event is represented by a sentence extracted from the collection. We have conducted some experiments showing the interest of the method for this issue. Our method is based on a combination of linguistic modeling (concerning temporal adverbial meanings), symbolic natural language processing techniques (using cascades of morpho-lexical transducers) and data mining techniques (namely, sequential pattern mining under constraints). The system was applied to a corpus of newswires in French provided by the Agence France Presse (AFP). Evaluation was performed in partnership with French newswire agency journalists.
URI : http://www.repositoriodigital.ipn.mx/handle/123456789/16621
ISSN : 1405-5546
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