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The Scientific World Journal
Volume 2014, Article ID 973750, 11 pages
http://dx.doi.org/10.1155/2014/973750
Research Article

Negative and Positive Association Rules Mining from Text Using Frequent and Infrequent Itemsets

1Department of Computer Science & Engineering, University of Engineering & Technology, Lahore, Pakistan
2Al-Khawarizmi Institute of Computer Sciences, UET, Lahore, Pakistan
3Ted Rogers School of Information Technology Management, Ryerson University, Toronto, Canada

Received 17 February 2014; Revised 27 March 2014; Accepted 1 April 2014; Published 18 May 2014

Academic Editor: Daniel D. Sánchez

Copyright © 2014 Sajid Mahmood et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Sajid Mahmood, Muhammad Shahbaz, and Aziz Guergachi, “Negative and Positive Association Rules Mining from Text Using Frequent and Infrequent Itemsets,” The Scientific World Journal, vol. 2014, Article ID 973750, 11 pages, 2014. https://doi.org/10.1155/2014/973750.