A Prefixed-Itemset-Based Improvement for Apriori Algorithm

摘要

Association rules is a very important part of data mining. It is used to find the interestingpatterns from transaction databases. Apriori algorithm is one of the most classical algorithmsof association rules, but it has the bottleneck in efficiency. In this article, we proposed aprefixed-itemset-based data structure for candidate itemset generation, with the help of thestructure we managed to improve the efficiency of the classical Apriori algorithm.