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Multi-Agent System for Arabic Text Categorization

  • Mounir Gouiouez
  • Meryeme Hadni
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 37)

Abstract

Developing TC systems for Arabic documents is a challenging task due to the complex and rich nature of the Arabic language, and the way in which they are written according to its position in the sentence. Furthermore, Arabic is written from right to left, and its letters changing form according to their position in the word. There are various different methods for text categorization, including distance-based, decision tree-based methods, Bayesian naïf…etc. Furthermore, the large numbers of methods proposed are typically based on the classical Bag-of-Words model. In order to improve the accuracy of Arabic text categorization, therefore the accuracy of the results obtained, a new hybrid approach is proposed to improve the effectiveness of the automated techniques categorization. This paper presents the development of a concept and an associated architecture called the CAMATC (Cooperative Adaptive Multi-Agent System for Arabic Text Categorization), which is based on the combination of Multi-Agent Systems and the conceptual representation in the Arabic text categorization.

Keywords

Text categorization Multi-Agent System Graph-based Named entities BabelNet 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.USMBAFezMorocco

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