A DEEP AUTOENCODER-BASED REPRESENTATION FOR ARABIC TEXT CATEGORIZATION

A DEEP AUTOENCODER-BASED REPRESENTATION FOR ARABIC TEXT CATEGORIZATION

Arabic text representation is a challenging assignment for several applications such as text categorization and clustering since the Arabic language is known for its variety, richness and complex morphology. Until recently, the Bag-of-Words remains the most common method for Arabic text representat...

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Bibliographic Details
Main Authors:	Fatima-zahra El-Alami, Abdelkader El Mahdaouy, Said Ouatik El Alaoui, Noureddine En-Nahnahi
Format:	Article
Language:	English
Published:	UUM Press 2020-06-01
Series:	Journal of ICT
Subjects:	Arabic text representation deep autoencoder feature selection machine learning text categorization
Online Access:	https://e-journal.uum.edu.my/index.php/jict/article/view/12388

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