Arabic script language identification using letter frequency neural networks

Article Properties
Abstract
Cite
Selamat, Ali, and Choon‐Ching Ng. “Arabic Script Language Identification Using Letter Frequency Neural Networks”. International Journal of Web Information Systems, vol. 4, no. 4, 2008, pp. 484-00, https://doi.org/10.1108/17440080810919503.
Selamat, A., & Ng, C. (2008). Arabic script language identification using letter frequency neural networks. International Journal of Web Information Systems, 4(4), 484-500. https://doi.org/10.1108/17440080810919503
Selamat A, Ng C. Arabic script language identification using letter frequency neural networks. International Journal of Web Information Systems. 2008;4(4):484-500.
Journal Category
Science
Science (General)
Cybernetics
Information theory
Refrences
Title Journal Journal Categories Citations Publication Date
10.1109/ODYSSEY.2006.248098
10.1023/A:1009982220290
Language identification in web documents using discrete HMMs Pattern Recognition
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Technology: Engineering (General). Civil engineering (General)
 13 2004
10.1007/978-3-540-30198-1_29
Data Mining: A Preprocessing Engine Journal of Computer Science 224 2006
Citations
Title Journal Journal Categories Citations Publication Date
ARABIC SCRIPT WEB PAGE LANGUAGE IDENTIFICATION USING HYBRID-KNN METHOD

 International Journal of Computational Intelligence and Applications
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 1 2009
Citations Analysis
Category Category Repetition
Science: Mathematics: Instruments and machines: Electronic computers. Computer science1
The category Science: Mathematics: Instruments and machines: Electronic computers. Computer science 1 is the most commonly referenced area in studies that cite this article.