A dynamic system for detecting and correcting spelling errors in Arabic texts using Levenshtein distance and dynamic programming

Ali Chachan, Fathala; Shnaishel Cheetar, Alaa; Ali Chachan, Fiaria

doi:10.33916/qjae.2026.023647

	A dynamic system for detecting and correcting spelling errors in Arabic texts using Levenshtein distance and dynamic programming
AL-Qadisiyah Journal For Administrative and Economic sciences
Volume 28, Issue 2, July 2026, Pages 36-47 PDF (1.3 M)
Document Type: Research Paper
DOI: 10.33916/qjae.2026.023647
Authors
Fathala ali Chachan¹; Alaa Shnaishel Cheetar²; Fiaria ali Chachan³
¹Dept. of Financial &Banking, College of Administration & Economics, Mustansiriyah University,Baghdad,Iraq.
²Dept. of Financial &Banking, College of Administration & Economics, Mustansiriyah University,Baghdad,Iraq
³Dept. of mathematics, College of science, Mustansiriyah University,Baghdad,Iraq.
Abstract
Arabic is tougher to spell check on computers than other languages because the letters are shaped and placed in a way that is different from other languages. The spelling and accuracy of Arabic information have a big effect on how well it is in academic research, government documents, and teaching materials. This is because spelling mistakes can make a piece of writing hard to read and understand or distort its meaning. We need clever technology that can automatically discover and rectify spelling issues in texts from multiple areas, including Word and PDF files or digital photos. The purpose of this work is to make an Arabic text processing system that employs both automatic spelling mistake detection and repair and statistical analysis to measure the quality of the text in numbers, such as the number of correct and incorrect words and the error rate. The system utilizes a significant amount of new technology. The system initially utilizes optical character recognition (OCR) to extract text from pictures and data.After that, it fixes any mistakes in the text using the ar corrector library, which has an Arabic dictionary. The whole cost falls down, and the words that were repaired are more correct. We utilize the Levenshtein distance from the original word to figure out how much each suggestion costs. We use dynamic programming to find the best arrangement of words in the whole text.
Keywords
Checking spelling; fixing text automatically; and dynamic programming

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