Research Article
A Novel Association Rule Algorithm to Discover Maximal Frequent Item Set
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 137 - Issue 9 |
| Published: March 2016 |
| Authors: Hartej Singh, Vinay Dwivedi |
10.5120/ijca2016908883
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Hartej Singh, Vinay Dwivedi . A Novel Association Rule Algorithm to Discover Maximal Frequent Item Set. International Journal of Computer Applications. 137, 9 (March 2016), 1-4. DOI=10.5120/ijca2016908883
@article{ 10.5120/ijca2016908883,
author = { Hartej Singh,Vinay Dwivedi },
title = { A Novel Association Rule Algorithm to Discover Maximal Frequent Item Set },
journal = { International Journal of Computer Applications },
year = { 2016 },
volume = { 137 },
number = { 9 },
pages = { 1-4 },
doi = { 10.5120/ijca2016908883 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2016
%A Hartej Singh
%A Vinay Dwivedi
%T A Novel Association Rule Algorithm to Discover Maximal Frequent Item Set%T
%J International Journal of Computer Applications
%V 137
%N 9
%P 1-4
%R 10.5120/ijca2016908883
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Association Rule mining is a sub-discipline of data mining. Apriori algorithm is one of the most popular association rule mining technique. Apriori technique has a disadvantage that before generating a maximal frequent set it generates all possible proper subsets of maximal set. Therefore it is very slow as it requires many database scans before generating a maximal frequent itemset In the method proposed in this paper entire database is scanned only once. Frequency count of all distinct transactions is stored in a hash map. Algorithm maintains an array of tables such that each table in the array contain frequency count of all potential k-itemsets..Binary search and the concept of longest common subsequence are used to efficiently extract maximal frequent itemset. Experimental results show that proposed algorithm performs better than apriori algorithm.
References
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