Evaluating the effectiveness of association rules mining algorithms in parallel processing environment - Nguyen, Dang Cam; Nguyen, Thanh Son (Journal of Technical Education Science, 2019)
An association rule indicates the relationship, association, or correlation between objects in the database. Association Rule Mining is a problem which has received an increasing amount of attention lately in data mining. Appriori and FP-Growth have commonly used algorithms in association rule mining. The aim of the paper is to evaluate the effectiveness of the Apriori, FP_Growth and Improved Apriori in a parallel processing environment. The comparison is based on execution time and the performance. The experimental results showed that in the parallel processing environment the FP-growth algorithm is the most efficient one.