Conference Proceedings

Abstract

In this paper we are trying to comparing the different sequential data mining algorithms for finding the frequent data patterns. There are many algorithms have designed for finding the frequent data patterns from the transactional database. Transactional database have specified number of transactions itemsets T, which are used for knowledge discovery. For Studying and Comparatively analysis purpose, we take three methods, one is traditional method Aprori and other two methods are 1. LCM (Linear closed itemset Miner) algorithm and 2. Top-K Closed Frequent pattern mining. Here we show the theoretically analysis of efficiency of different algorithms with computational complexity compared