|Communications on Applied Electronics|
|Foundation of Computer Science (FCS), NY, USA|
|Volume 3 - Number 5|
|Year of Publication: 2015|
|Authors: Amritpal Kaur, Vaishali Aggarwal|
Amritpal Kaur, Vaishali Aggarwal . Frequent Item Set Mining using Association Rules. Communications on Applied Electronics. 3, 5 ( November 2015), 18-20. DOI=10.5120/cae2015651945
One of the most difficult tasks in data mining is to fetch the frequent item set from large database. Related to this many conquering algorithms have been introduced till now. Whereas frequent item set figures out pattern, correlation as well as association between items in a bulky database and these constraints provides better scope in mining process. During study it has been founded that either support count or candidate count are been taken into consideration by using less and strong association rules. But this approach doesn’t improve time parameter (which seems to be constant). Our proposed work is based on reducing time component by considering both pre and post processing results in each transaction. As a result frequent item set will be formed by applying further strong association rules with the help of pre defined support and candidate count. In result this approach will acquire better performance.