Universiti Teknologi Malaysia Institutional Repository

Arabic language script and encoding identification with support vector machines and rough set theory

Mohamed Sidya, Mohamed Ould (2007) Arabic language script and encoding identification with support vector machines and rough set theory. Masters thesis, Universiti Teknologi Malaysia, Faculty of Computer Science and Information System.


Official URL: http://dms.library.utm.my:8080/vital/access/manage...


Arabic is ranking sixth among the world’s spoken languages with more than 230 million speakers around the Arabic world. There are different flavors and dialects of Arabic; the most common one is the Egyptian Arabic which has the largest number of users (more than 50 millions). Although, only a small number Arabic speakers use the internet, still it constitutes a considerable share to the internet community. Unfortunately, so far, there has been no research to automatically distinguish between the Arabic language and the other languages that use the same script. This project deals with identifying the Arabic language from the Persian language; both languages are written in the Arabic script. The data for this project has been collected from the internet, the BBC website in particular. Many operations have been applied to this data, including stop word removal and stemming. This project is established to compare the performance of Support Vector Machines with Rough Set Theory in Identifying the Arabic language. The results show that both methods perform well but the Support Vector Machines outperform the Rough Set Theory.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Sains (Sains Komputer)) - Universiti Teknologi Malaysia, 2007; Supervisor : Dr. Ali Bin Selamat
Uncontrolled Keywords:Rough Set Theory, Arabic language, Support Vector Machines
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System
ID Code:6795
Deposited By: Narimah Nawil
Deposited On:25 Nov 2008 03:23
Last Modified:03 Aug 2018 08:49

Repository Staff Only: item control page