IJCCE 2012 Vol.1(1): 28-30 ISSN: 2010-3743
DOI: 10.7763/IJCCE.2012.V1.9
DOI: 10.7763/IJCCE.2012.V1.9
Association Rules Mining for Urdu Language
Nazish Asad, M. Younus Javed, and Usman Qamar
Abstract—This paper explains the importance of Association Rules for several domains of Urdu language (e.g. education, publication and web development). Although various association rules mining techniques have successfully used for market basket analysis but no one has applied on Urdu text. A new mining model i.e. Urdu Mining Model (UMM) is proposed based upon Apriori algorithm and used to extract unique words and phrases from Urdu language. UMM is tested on an Urdu corpus and results have shown that it has worked well on Urdu text i.e. Apriori is really effective to mine text databases as well. Results are communicated for further research and enhancement of existing tools and systems which deal Urdu text in one way or the other.
Index Terms—Urdu language, association rules mining, apriori algorithm.
Authors are with the Department of Computer Engineering, College of Electrical and Mechanical Engineering, National University of Sciences and Technology (NUST), Islamabad, Pakistan (e-mail: nasad887@gmail.com, myjaved@ceme.nust.edu.pk, usman_zaman@yahoo.com).
Cite: Nazish Asad, M. Younus Javed, and Usman Qamar, "Association Rules Mining for Urdu Language," International Journal of Computer and Communication Engineering vol. 1, no. 1, pp. 28-30 , 2012.
General Information
ISSN: 2010-3743 (Online)
Abbreviated Title: Int. J. Comput. Commun. Eng.
Frequency: Quarterly
DOI: 10.17706/IJCCE
Editor-in-Chief: Dr. Maode Ma
Abstracting/ Indexing: INSPEC, CNKI, Google Scholar, Crossref, EBSCO, ProQuest, and Electronic Journals Library
E-mail: ijcce@iap.org
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