CIDE (2002) Fellah
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ArabTDM: Automatic recognition of arabic contents of scientific journals
Titre du document / Document title ArabTDM: Automatic recognition of arabic contents of scientific journals Auteur(s) / Author(s) FELLAH Meriem (1) ; ANJA HABACHA CHAIBI (1) ; MOHAMED BEN AHMED (1) ; Affiliation(s) du ou des auteurs / Author(s) Affiliation(s) (1) RIADI/ENSI, University of La Manouba, TUNISIE Résumé / Abstract The work presented in this paper tackling the document analysis and recognition problem, in line with a virtual library project. It presents the design and the implementation of an automatic recognition system of the contents of scientific journals written in Arabic. The system deals with homogeneous and intermediary contents. Its based on an hybrid approach which integrates the top-down approach for the segmentation of the digitised contents into significant blocs and the extraction of the main bloc, and the bottom-up approach which considers the text file representing the body of the contents and uses the tagging technique to extract its different items and to distinguish their relating components: Title, Author(s) and Page numbers. The output of the system is a HTML (HyperText Markup Language) file stored into a database with appropriate hyperlinks. Source / Source Congrès Documents dans les systèmes d'information mobiles : ( Hammamet, 20-23 octobre 2002 ) CIDE : colloque international sur le document électronique No5, Hammamet , TUNISIE (20/10/2002) 2002 , pp. 83-96[Note(s) : [308 p.]] [Document : 14 p.] (8 ref.) ISBN 2-7261-1223-4 ; Illustration : Illustration ; Langue / Language Anglais Revue : Français Editeur / Publisher INRIA, Le Chesnay, FRANCE (2002) (Monographie) Mots-clés anglais / English Keywords HTML language ; Segmentation ; Content analysis ; Arabic ; Language ; Periodical ; Scientific literature ; Optical character recognition ; Mots-clés français / French Keywords Langage HTML ; Segmentation ; Analyse contenu ; Arabe ; Langage ; Périodique ; Littérature scientifique ; Reconnaissance optique caractère ; Mots-clés espagnols / Spanish Keywords Lenguaje HTML ; Segmentación ; Análisis contenido ; Árabe ; Lenguaje ; Periódico ; Literatura científica ; Reconocimento óptico de caracteres ; Localisation / Location INIST-CNRS, Cote INIST : Y 34559, 35400010854579.0060
