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