An Improved Apriori Algorithm Based on Association Analysis

Abstract

Association Rules Mining is an important branch of Data Mining Technology, of which Apriori Algorithm is the most influential and classic one. After discussing and analyzing the basic concept of Association Rules Mining, this paper proposes an improved algorithm based on a combination of Data Division and Dynamic Item sets Counting. Analysis of the improved algorithm proves that it can effectively improve the performance of Data Mining.