一种快速最大频繁序列模式挖掘算法

A Mining Algorithm for Fast Maximal Sequential Patterns

针对序列模式挖掘中,频繁子序列个数随模式长度增加而爆炸性增长的问题,提出一种从序列数据库中挖掘最大频繁序列模式的新算法(MFSPAN).MFSPAN充分利用不同序列可能具有相同前缀的性质来减少项集比较次数.在标准测试数据集上的实验结果表明了MFSPAN的有效性.

This paper proposes a novel algorithm MFSPAN （maximal frequent sequential pattern mining algorithm）. MFSPAN is used to mine the complete set of maximal frequent sequential patterns in sequence databases. It solves the problem that the number of frequent subsequences will increase explosively as frequent patterns become longer： because MFSPAN takes full advantage of the property that different sequences may share a common prefix to reduce itemset comparing times. Experiments on standard test data show that MFSPAN is very effective.