The week's pick
Reseach Article
Association Rules Optimization using Artificial Bee Colony Algorithm with Mutation
| 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
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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