Analyzing Calendar based Association Rule Using FP-growth Algorithm

Abstract

This paper is presented the mining association rules among items in a large database of sales transactions. The mining of association rules can be mapped into the problem of discovering large itemsets which appear in a sufficient number of transactions. Association rule mining plays an essential role in data mining. The knowledge used for mining rule depends on time(month, season) in real world and so calendar based association rule is needed to consider. Calendar pattern is used to restrict the time interval. Calendar based association rules is an interesting extension to association rules by including a calendar pattern. Frequent-Pattern Growth (FP-Growth) algorithm is used to generate the calendar based association rules. FP-Growth is a method of mining frequent itemsets without candidate generation. The system generates the calendar based association rule using FP-Growth algorithm and analyze on the result.