关键词: 数据挖掘, 关联规则, Apriori算法, 数据压缩, 频繁集检测

Abstract: The Apriori algorithm is one of the most influential algorithms for mining association rules. It can work on the large dataset efficiently. However, the traditional?Apriori algorithm?has two?bottlenecks. It generates a?large number of?candidate?sets, and most of them are useless. It has to scan?the database for many times. This paper presents an improved Apriori algorithm based on the data compression methodology. The improved algorithm can reduce the number of database scans and the number of candidate set by pre-judging at the same time. Complicated experiment demonstrates that a significant improvement has been achieved by the algorithm.

Key words: data mining, association rules, Apriori, data compression, detection of frequent set