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Spelling Detection Errors Techniques in NLP: A Survey

by Rasha Altarawneh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 172 - Number 4
Year of Publication: 2017
Authors: Rasha Altarawneh
10.5120/ijca2017915176

Rasha Altarawneh . Spelling Detection Errors Techniques in NLP: A Survey. International Journal of Computer Applications. 172, 4 ( Aug 2017), 1-5. DOI=10.5120/ijca2017915176

@article{ 10.5120/ijca2017915176,
author = { Rasha Altarawneh },
title = { Spelling Detection Errors Techniques in NLP: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2017 },
volume = { 172 },
number = { 4 },
month = { Aug },
year = { 2017 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume172/number4/28236-2017915176/ },
doi = { 10.5120/ijca2017915176 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:19:24.450064+05:30
%A Rasha Altarawneh
%T Spelling Detection Errors Techniques in NLP: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 172
%N 4
%P 1-5
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper reports the efforts of Arabic Spell-checker researches by providing a brief summary of proposed methods and techniques that explains how the spelling errors might be discovered in any entered text. It mainly unites two areas that are quite different in appearance, computer science and natural languages .The domain of this topic is limited because of the complex morphology it has compared with other Languages, and the variation of its stems and the similarity of the characters for this language. This poses a challenge for the researchers to concern about it.

References
  1. Majed Al-Jefri and Sabri Mahmoud. Context-sensitive arabic spell checker using context words and n-gram language models. 2013.
  2. Rasha AL-Tarawneh, Hatem S. A. Hamatta, and Hasan Muiadi. Novel approach for arabic spell-checker: Based on radix search tree. IJCA, 95:5, 2014.
  3. Bassam Haddad and Mustafa Yaseen. Detection and correction of non-words in arabic :a hybrid approach. International Journal of Computer Processing of Oriental Languages, 20, 2007.
  4. Bakkali Hamza, Gueddah Hicham, Yousfi Abdellah, and Belkasmi Mostafa. For an independent spell-checking system from the arabic language vocabulary. (IJACSA) International Journal of Advanced Computer Science and Applications, 5:4, 2014.
  5. AbdAllah Gomah Khaled Shaalan, Amin Allam. Towards automatic spell checking for arabic. 2003.
  6. Hasan Muaidi and Rasha Al-Tarawneh. Towards arabic spellchecker based on n-grams scores. IJCA, 53:5, 2012.
  7. JOSEPH J. POLLOCK and ANTONIO ZAMORA. Automatic spelling correction in scientific and scholarly text. Communications of the ACM, 27:11, 1984.
  8. Zeina Azzam Seikaly. The arabic language: The glue that binds the arab world. AMIDEAST.
  9. Khaled Shaalan, Younes Samih, Mohammed Attia, Pavel Pecina, and Josef van Genabith. Improved spelling error detection and correction for arabic. Council for Science Engineering and Technology, page 7, 2011.
  10. Amar Balla Taha Zerrouki. Implementation of infixes and circumfixes in the spellcheckers. 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Spell-Checker Natural Language N-gram Radix tree Context text

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