Models & Optimisation and Mathematical Analysis Journal
Volume 7, Numéro 1, Pages 26-29
2019-12-24
An Empirical Study On The Effect Of Weighting Schemes And Machine Learning Algorithms On The Arabic Text Classification
Authors : Bennabi Rim Sakina . Elberrichi Zakaria .
Abstract
Nowadays, many applications use text classification to categorize different documents with predefined labels. However, most of the work focuses on the English language and a small number of studies focus on the Arabic language. The latter is widely used on the Internet and has a complex morphology that needs to be studied in different manners. In this context, we propose in this paper an empirical study on the effect of the use of different learning algorithms (SVM, Naive Bayes and KNN) and different weighting methods (TC, TF and TF.IDF) on Arabic textual classification . The goal of our work is to find the best combination that enhance the performance. The results show that SVM and TF.IDF combination offers the best accuracy and F-Measure (94%).
Keywords
weighting schemes ; NB ; SVM ; KNN ; Arabic text classification
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