Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
An enormous amount of valuable human knowledge is preserved in documents. The rapid growth in the number of machine-readable documents for public or private access requires the use of automatic text classification. Text classification can be defined as assigning or structuring documents into a defined set of classes known in advance. Arabic text classification methods have emerged as a natural result of the existence of a massive amount of varied textual information written in the Arabic language on the web. This study presents a review on the published researches of Arabic text classification using classical data representation, Bag of Words (BoW) and using conceptual data representation based on semantic resources such as Arabic WordNet and Wikipedia.
How to cite this article:
Musab Mustafa Hijazi, Akram M. Zeki and Amelia Ritahani Ismail. Arabic Text Classification: Review Study.
DOI: https://doi.org/10.36478/jeasci.2016.528.536
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2016.528.536