• DocumentCode
    2339680
  • Title

    Text thematic fragmentation and identification

  • Author

    Mahmoudi, Khaoula ; Faiz, Sami

  • Author_Institution
    URISA, Ecole Super. des Commun. de Tunis (SUPCOM), El Ghazala Ariana, Tunisia
  • fYear
    2010
  • fDate
    16-19 May 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Given the exponential growth of online information, one of the primary difficulties facing users is the information overload. Huge amounts of these electronic information are mainly encapsulated in text documents. So, the researchers are striving to develop robust methods to provide users and managers with prominent solutions needed for text analysis. This allows maximizing profits by saving time and money devoted to manage the increasing amount of information. In this context and among others we find text segmentation and theme identification. In this paper and by resting on the existing well known approaches and advances in the text segmentation and theme identification fields, we propose new solutions to reach the objectives behind achieving these two techniques more accurately.
  • Keywords
    identification; text analysis; electronic information; information overload; online information; text analysis; text document; text segmentation; text thematic fragmentation; theme identification; Object recognition; C99; TextTiling; WordNet; frequency counting; text segmentation; theme identificatiot;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Systems and Applications (AICCSA), 2010 IEEE/ACS International Conference on
  • Conference_Location
    Hammamet
  • Print_ISBN
    978-1-4244-7716-6
  • Type

    conf

  • DOI
    10.1109/AICCSA.2010.5587007
  • Filename
    5587007