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RÉGAL, un système pour la visualisation sélective de documents
Author(s) -
Javier Couto,
Olivier Ferret,
Brigitte Grau,
Nicolás Hernández,
Agata Jackiewicz,
Jean-Luc Minel,
Sylvie Porhiel
Publication year - 2004
Publication title -
revue d intelligence artificielle
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.146
H-Index - 14
eISSN - 1958-5748
pISSN - 0992-499X
DOI - 10.3166/ria.18.481-514
Subject(s) - computer science , information retrieval , cohesion (chemistry) , visualization , disk formatting , relevance (law) , snippet , world wide web , structuring , artificial intelligence , chemistry , organic chemistry , finance , political science , law , economics , operating system
Information retrieval systems generally return a list of ranked documents, such as only the title and possibly a snippet that contains the words of the request allow a user to evaluate the document relevance relative to her initial request. This kind of result leads the user to browse a lot of documents before satisfying her information need. In order to improve information retrieval, we have studied text visualization: which information has to be shown and how? Our system REGAL (REsume Guide par les Attentes du Lecteur), automatically extracts the visualized information from texts by applying a thematic analysis that does not require a pre-existing structuring or a formatting of the texts, and is based on the combination of two criteria: lexical cohesion and cue phrases. MOTS-CLES : visualisation de texte, navigation textuelle, resume dynamique, analyse thematique.

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