Qur'anic words stemming

Raja Yusof, Raja Jamilah and Zainuddin, R. and Baba, Mohd Sapiyan and Yusoff, Z.M. (2010) Qur'anic words stemming. Arabian Journal for Science and Engineering, 35 (2C). pp. 37-49. ISSN 2193-567X,

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Arabic words are known to have complex morphological structure. The different structures produce various word patterns or derivatives from a root word. This paper attempts to identify various word patterns that originate from a root word. These word patterns are compared to the words in the 30th part of the Qur'an. Nine stemming test cases were outlined for words in the 30 th part of the Qur'an. Analysis showed that stemming nouns and particles leads to a lower percentage error compared to stemming the 10 alphabets that can be added as affixes in a root word. A rule-based stemming engine (RSE) was also implemented and the stemming accuracy achieved was 62.5 and the average time taken to stem 1000 word tokens was 11.7ms. The accuracy of the results was comparable to other stemming engines such as the Khoja stemmer, Buckwalter Morphological Analyzer (BAMA), Tri-literal Root Extraction (TRE) algorithm, and Voting algorithm.

Item Type: Article
Additional Information: Export Date: 7 November 2012 Source: Scopus Language of Original Document: English Correspondence Address: Yusof, R.J.R.; Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia; email: rjry@um.edu.my References: Dukes, K., Atwell, E., Sharaf, A.M., Syntactic Annotation Guidelines for the Quranic Arabic Treebank (2010) The Seventh International Conference on Language Resources and Evaluation (LREC-2010); Maamouri, M., Bies, A., Buckwalter, T., Mekki, W., The Penn Arabic Treebank: Building a Large-Scale Annotated Arabic Corpus (2004) Proc. of the Arabic Language Technologies and Resources Int'l. Conference; NEMLAR, , http://papers.LDC.uPenn.edu/NEMLAR2004/Penn-Arabic-Treebank.pdf; Buckwalter, T., Issues in Morphological Analysis (2007) Arabic Computational Morphology, pp. 23-41. , Eds. A. Soudi, A. van den Bosch, and G. Neumann. 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Uncontrolled Keywords: Arabic stemming; Arabic word morphology; Qur'an; Rule-Based algorithm
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Computer Science & Information Technology > Department of Artificial Intelligence
Depositing User: Ms Maisarah Mohd Muksin
Date Deposited: 04 Jan 2013 16:48
Last Modified: 30 Apr 2021 00:43
URI: http://eprints.um.edu.my/id/eprint/5673

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