Arabic language script and encoding identification with support vector machines and rough set theory
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 sma...
Saved in:
Main Author: | Mohamed Sidya, Mohamed Ould |
---|---|
Format: | Thesis |
Language: | English |
Published: |
2007
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/6795/1/MohamedOuldMohamedSidyaMFSKSM2007.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Rough sets theory for travel demand analysis in Malaysia
by: Wong, Jenn Hwee
Published: (2008) -
Trademark image classification approaches using neural network and rough set theory
by: Saad, Puteh
Published: (2003) -
Plagiarism auto-detection in Arabic scripts using statement-based fingerprints matching and fuzzy-set information retrieval
by: Mohammed Alzahrani, Salha
Published: (2009) -
Email categorization using support vector machine
by: Mohd. Daud, Mariah
Published: (2004) -
Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory
by: Lim, Khai Yin
Published: (2017)