Identifying Strategic Information from Scientific Articles through Sentence Classification.

Fidelia Ibekwe-Sanjuan 1, * Chaomei Chen 2 Pinho Roberto 3
* Corresponding author
1 ELICO Lyon 3
ELICO - Equipe de recherche de Lyon en sciences de l'information et de la communication
Abstract : We address here the need to assist users in rapidly accessing the most important or strategic information in the text corpus by identifying sentences carrying specific information. More precisely, we want to identify contribution of authors of scientific papers through a categorization of sentences using rhetorical and lexical cues. We built local grammars to annotate sentences in the corpus according to their rhetorical status: objective, new things, results, findings, hypotheses, conclusion, related_word, future work. The annotation is automatically projected automatically onto two other corpora to test their portability across several domains. The local grammars are implemented in the Unitex system. After sentence categorization, the annotated sentences are clustered and users can navigate the result by accessing specific information types. The results can be used for advanced information retrieval purposes.
Document type :
Conference papers
6th International Conference on Language Resources and Evaluation Conference (LREC-08), May 2008, Marrakesh, Morocco. ELDA, pp.1518-1522, 2008


https://hal.archives-ouvertes.fr/hal-00635663
Contributor : Fidelia Ibekwe-SanJuan <>
Submitted on : Tuesday, October 25, 2011 - 4:45:41 PM
Last modification on : Tuesday, February 3, 2015 - 3:49:55 PM

File

LREC08-published-version.pdf
fileSource_public_author

Identifiers

  • HAL Id : hal-00635663, version 1

Collections

Citation

Fidelia Ibekwe-Sanjuan, Chaomei Chen, Pinho Roberto. Identifying Strategic Information from Scientific Articles through Sentence Classification.. 6th International Conference on Language Resources and Evaluation Conference (LREC-08), May 2008, Marrakesh, Morocco. ELDA, pp.1518-1522, 2008. <hal-00635663>

Export

Share

Metrics

Consultation de
la notice

117

Téléchargement du document

24