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Association Rules Optimization using Artificial Bee Colony Algorithm with Mutation

by Pankaj Sharma, Sandeep Tiwari, Manish Gupta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 116 - Number 13
Year of Publication: 2015
Authors: Pankaj Sharma, Sandeep Tiwari, Manish Gupta
10.5120/20399-2705

Pankaj Sharma, Sandeep Tiwari, Manish Gupta . Association Rules Optimization using Artificial Bee Colony Algorithm with Mutation. International Journal of Computer Applications. 116, 13 ( April 2015), 29-31. DOI=10.5120/20399-2705

@article{ 10.5120/20399-2705,
author = { Pankaj Sharma, Sandeep Tiwari, Manish Gupta },
title = { Association Rules Optimization using Artificial Bee Colony Algorithm with Mutation },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 116 },
number = { 13 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 29-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume116/number13/20399-2705/ },
doi = { 10.5120/20399-2705 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:57:03.594054+05:30
%A Pankaj Sharma
%A Sandeep Tiwari
%A Manish Gupta
%T Association Rules Optimization using Artificial Bee Colony Algorithm with Mutation
%J International Journal of Computer Applications
%@ 0975-8887
%V 116
%N 13
%P 29-31
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In data mining, Association rule mining is one of the popular and simple method to find the frequent item sets from a large dataset. While generating frequent item sets from a large dataset using association rule mining, computer takes too much time. This can be improved by using artificial bee colony algorithm (ABC). The Artificial bee colony algorithm is an optimization algorithm based on the foraging behavior of artificial honey bees. In this paper, artificial bee colony algorithm with mutation operator is used to generate high quality association rules for finding frequent item sets from large data sets. The mutation operator is used after the scout bee phase in this work. In general the rule generated by association rule mining technique do not consider the negative occurrences of attributes in them, but by using artificial bee colony algorithm (ABC) over these rules the system can predict the rules which contains negative attributes.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial bee colony (ABC) Mutation Association rule Support Confidence Frequent item set Data mining.