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General Information
    • ISSN: 2010-3751
    • Frequency: Bimonthly (2012-2016); Quarterly (Since 2017)
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Mohamed Othman
    • Executive Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: Google Scholar, Engineering & Technology Digital Library, and Crossref, DOAJ, Electronic Journals LibraryEI (INSPEC, IET).
    • E-mail:  ijfcc@ejournal.net 
Editor-in-chief
Prof. Mohamed Othman
Department of Communication Technology and Network Universiti Putra Malaysia, Malaysia
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.
IJFCC 2013 Vol.2(4): 355-358 ISSN: 2010-3751
DOI: 10.7763/IJFCC.2013.V2.184

A New Efficient Matrix Based Frequent Itemset Mining Algorithm with Tags

Harpreet Singh and Renu Dhir
Abstract—The main aim of this paper is to present a new method based on transactional matrix and transaction reduction for finding frequent itemsets more efficiently. The association rule mining is based mainly on discovering frequent itemsets. Apriori algorithm is the most classical algorithm in association rule mining, but it has two fatal deficiencies: generation of a large number of candidate itemsets and scanning the database too many times. Apriori and other popular association rule mining algorithms mainly generate a large number of candidate 2-itemsets. To remove these deficiencies, a new method named Matrix Based Algorithm with Tags (MBAT) is proposed in this paper which finds the frequent itemsets directly from the transactional matrix which is generated from the database to generate association rules. Proposed algorithm greatly reduces the number of candidate itemsets, mainly candidate 2-itemsets

Index Terms—Apriori algorithm, Association rule, Frequent itemsets, Transactional matrix, Transaction reduction

The authors are with the Department of Computer Science and Engineering, National Institute of Technology, Jalandhar, India (e-mail: harpreet99.nitj@gmail.com; dhirr@nitj.ac.in).

[PDF]

Cite: Harpreet Singh and Renu Dhir, "A New Efficient Matrix Based Frequent Itemset Mining Algorithm with Tags," International Journal of Future Computer and Communication vol. 2, no. 4 pp. 355-358, 2013.
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