A DEEP AUTOENCODER-BASED REPRESENTATION FOR ARABIC TEXT CATEGORIZATION-Reference-Cited by-同舟云学术

A DEEP AUTOENCODER-BASED REPRESENTATION FOR ARABIC TEXT CATEGORIZATION

Published:2020-06 Issue:3 Volume:19 Page:381-398
ISSN:2180-3862
Container-title:Journal of Information and Communication Technology
language:en
Short-container-title:JICT

Author:

El-Alami Fatima-zahra¹,El Mahdaouy Abdelkader¹,El Alaoui Said Ouatik²,En-Nahnahi Noureddine¹

Affiliation:

1. Laboratory of Informatics and Modeling, FSDM, Sidi Mohamed Ben Abdellah University, Morocco

2. Laboratory of Informatics and Modeling, FSDM, Sidi Mohamed Ben Abdellah University, Morocco & National School of Applied Sciences, Ibn Tofail University, Morocco

Publisher

UUM Press, Universiti Utara Malaysia

Subject

General Mathematics,General Computer Science

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep ensemble transfer learning framework for COVID-19 Arabic text identification via deep active learning and text data augmentation;Multimedia Tools and Applications;2024-03-05

2. Natural Language Processing to Detect Fake News in Arabic: A Survey Paper;2023 3rd International Conference on Computing and Information Technology (ICCIT);2023-09-13

3. Novel Machine Learning–Based Approach for Arabic Text Classification Using Stylistic and Semantic Features;Computers, Materials & Continua;2023

4. A Review Study on Arabic Text Classification;2022 International Arab Conference on Information Technology (ACIT);2022-11-22

5. An unsupervised annotation of Arabic texts using multi-label topic modeling and genetic algorithm;Expert Systems with Applications;2022-10