Closed Regular Pattern Mining Using Vertical Format

Discovering interesting patterns in transactional databases is often a challenging area by the length of patterns and number of transactions in data mining, which is prohibitively expensive in both time and space. Closed itemset mining is introduced from traditional frequent pattern mining and having its own importance in data mining applications. Recently, regular itemset mining gained lot of attention in data mining research because of its occurrence behavior. In this paper we propose a new method called CRP-method (closed regular pattern method) to mine closed regular itemsets in transactional database by using vertical data format. Our CRP-method generates complete set of -closed regular patterns in transactional databases for a user given regularity threshold and support. Our experimental results show that this method is efficient in memory and execution time.