A Dynamically Mining Association Rules Algorithm Based on Binary Tree Coding and Its Application in Sale of Goods

Abstract

In order to solve the problem of mining association rules for database which has a small quantity of itemsets and a large quantity of transactions, this paper proposes a dynamical algorithm based on binary tree coding. It can be dynamically mining association rules through steps. Firstly, we set up a Binary Tree corresponding with itemset of a database. Secondly, we define an array for counting which is corresponding with itemset. Then scanning and counting the transaction records. Finally, analyzing and calculating the association rules. The algorithm takes full advantages of the characteristics of binary tree coding so that it can reduce I/O workload. It is easy to add or delete records at any time. Also it is easy to divide and merge data. The algorithm shows good application prospect.