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
Link To Document :
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