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26 mai 2008
- handle: 10670/1.gmhmyv
- hal: hal-00635663
info:eu-repo/semantics/OpenAccess
Mots-clés
sentence categorization lexical cues discourse analysis rhetorical cues sentence annotationSujets proches
Work, Method of Industry (Psychology) Method of work Natural science Sciences Science of science Papers Data retrieval Retrieval of information Information storage and retrieval Data storage Discourse grammar Text grammar Knowledge, Classification of WritersCiter ce document
Fidelia Ibekwe-Sanjuan et al., « Identifying Strategic Information from Scientific Articles through Sentence Classification. », HAL-SHS : sciences de l'information, de la communication et des bibliothèques, ID : 10670/1.gmhmyv
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Résumé
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.