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Decision Support System Tool for Arabic Text Recognition

Fatmah Baothman*, Sarah Alssagaff, Bayan Ashmeel

Information System Department, King Abdul-Aziz University, Jeddah, 21551, Saudi Arabia

* Corresponding Author: Fatmah Baothman. Email: email

(This article belongs to the Special Issue: Computational Intelligence for Internet of Medical Things and Big Data Analytics)

Intelligent Automation & Soft Computing 2021, 27(2), 519-531.


The National Center for Education Statistics study reported that 80% of students change their major or institution at least once before getting a degree, which requires a course equivalency process. This error-prone process varies among disciplines, institutions, regions, and countries and requires effort and time. Therefore, this study aims to overcome these issues by developing a decision support tool called TiMELY for automatic Arabic text recognition using artificial intelligence techniques. The developed tool can process a complete document analysis for several course descriptions in multiple file formats, such as Word, Text, Pages, JPEG, GIF, and JPG. We applied a comparative approach in selecting the highest score using three Arabic text extraction algorithms: term frequency-inverse document frequency measure algorithm, tool with Retina Database, and keyword extraction using word co-occurrence algorithm. The data repository consisted of 1000 datasets built from five different faculties at King Abdul-Aziz University and King Faisal University. It was followed by a discussion of the evaluation techniques using precision and recall measurements, which indicated that the keyword extraction using word co-occurrence algorithm scored 90% for the English language and 80% for the Arabic language in terms of the F1 measure that focuses on the linguistic relation between words.


Cite This Article

APA Style
Baothman, F., Alssagaff, S., Ashmeel, B. (2021). Decision support system tool for arabic text recognition. Intelligent Automation & Soft Computing, 27(2), 519-531.
Vancouver Style
Baothman F, Alssagaff S, Ashmeel B. Decision support system tool for arabic text recognition. Intell Automat Soft Comput . 2021;27(2):519-531
IEEE Style
F. Baothman, S. Alssagaff, and B. Ashmeel "Decision Support System Tool for Arabic Text Recognition," Intell. Automat. Soft Comput. , vol. 27, no. 2, pp. 519-531. 2021.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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