关键词: 数据挖掘, 频繁项集, 项集数组, 逻辑运算, 关联规则

Abstract: Discovering frequent item sets is the main way of association rules mining, and it is also the focus of the study in algorithms for association rules mining. The classical Apriori algorithm and its improved algorithms of association rules mining can be generally classified as one based on SQL and the other based on memory. To improve the data-mining efficiency, the authors proposed an efficient algorithm for discovering frequent item sets. After analyzing the efficiency bottlenecks in some algorithms based on memory, the algorithm used a method that could generate and test candidate item sets efficiently to optimize the speed of item sets generation. The experimental results show that the proposed algorithm can assuredly improve the mining efficiency.

Key words: data mining, frequent item set, item sets array, logic operation, association rule