NDLI: Capturing the Common Syntactical Rules for the Holy Quran: A Data Mining Approach

Content Provider	IEEE Xplore Digital Library
Author	Alsaheb, M.H. AbuZeina, D.E.M.A.
Copyright Year	2013
Description	Author affiliation: Coll. of IT & Comput. Eng., Polytech. Univ., Hebron, Palestinian Authority (Alsaheb, M.H.; AbuZeina, D.E.M.A.)
Abstract	This paper presents a novel approach to capture the common syntactical rules for the Holy Quran . By syntactical rules, we mean the common relationships between the words' tags that highly show up in the Quran. Arabic, like other language, has a number of tags which include nouns, verbs, and pronouns with a number of sub-types of each one of them. In this paper we used data mining approach to extract the common syntactical rules which will be offered to the natural language processing applications. Stanford part of speech tagger (29 tags) will be used to tag the Quran words. Then, the data mining too called WEKA (PredictiveApriori algorithm) will be used to find the famous syntactical rules. The extracted syntactical rules have a property that it is not necessary to have adjacent words tags. That is, long distance relation. The most common syntactical rule found is: tag1=RP tag2=NN tag3=WP 91 ⇒ tag4=VBD 90 acc:(0.97912)Which can be seen in the Quran sentence. This phrase (which is part of an ayah) appeared in 89 ayahs in 20 different surahs; the study used Mushaf Al-Madinah Al-Munawwarah (published by the King Fahd Complex for Printing the Holy Quran ).
Starting Page	670
Ending Page	680
File Size	199561
Page Count	11
File Format	PDF
e-ISBN	9781479928231
DOI	10.1109/NOORIC.2013.105
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-22
Publisher Place	Saudi Arabia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computers Printing Morphological Structures Arabic Language Syntactical Rules The Holy Quran Speech Prediction algorithms Data Mining Natural language processing Data mining Part of Speech Taggers.
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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