Arabic Text Categorization Using Support vector machine, Naïve Bayes and Neural Network

Author:

Mohammad Adel Hamdan,Alwada‘n Tariq,Al-Momani Omar

Abstract

Abstract Text classification is a very important area in information retrieval. Text classification techniques used to classify documents into a set of predefined categories. There are several techniques and methods used to classify data and in fact there are many researches talks about English text classification. Unfortunately, few researches talks about Arabic text classification. This paper talks about three well-known techniques used to classify data. These three well-known techniques are applied on Arabic data set. A comparative study is made between these three techniques. Also this study used fixed number of documents for all categories of documents in training and testing phase. The result shows that the Support Vector machine gives the best results.

Publisher

Springer Science and Business Media LLC

Reference43 articles.

1. Motaz K Saad, Wesam Ashour, “Arabic Text Classification Using Decision Trees”(2010) proceedings of the 12th international workshop on computer science and information technologies CSIT’2010, Moscow—Saint-Petersburg, Russia, 2010

2. Mofleh Al-diabat (2012),” Arabic Text Categorization Using Classification Rule Mining “Applied Mathematical Sciences, Vol. 6, 2012, no. 81,pp. 4033-404.

3. Sebastiani, F. (2002) ’Machine learning in automated text categorization’ ACM Publication:. ACM Computing Surveys, Vol. 34, No. 1, March 2002, pp. 1-4.

4. Rasha Elhassan, Mahmoud Ahmed (2015),” Arabic Text Classification review “ International Journal of Computer Science and Software Engineering (IJCSSE), Volume 4, Issue 1, January 2015

5. Adel Hamdan,, Raed Abu-Zitar “Spam Detection Using Assisted Artificial immune System”, Volume: 25, Issue: 8(2011) pp. 1275–1295, International Journal of Pattern Recognition and Artificial Intelligence,.

Cited by 43 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. Hybrid evolutionary machine learning model for advanced intrusion detection architecture for cyber threat identification;PLOS ONE;2024-09-12

2. Bio-Inspired Metaheuristic Algorithm for Network Intrusion Detection System of Architecture;Advances in Computational Intelligence and Robotics;2024-05-14

3. An Ensemble Method for Heterogeneous Data Classification using Boosted k-NN with Active Learning;2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT);2024-01-11

4. Utilizing Deep Learning Models (RNN, LSTM, CNN-LSTM, and Bi-LSTM) for Arabic Text Classification;Studies in Systems, Decision and Control;2024

5. An Empirical Investigation of the Use of ML and Neural Networks in English Learning;2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON);2023-12-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3