计算机科学 ›› 2015, Vol. 42 ›› Issue (5): 260-264.doi: 10.11896/j.issn.1002-137X.2015.05.052
刘端阳,冯 建,李晓粉
LIU Duan-yang, FENG Jian and LI Xiao-fen
摘要： 传统的类Apriori频繁序列模式挖掘算法都是基于支持度框架理论,需要预先设定支持度阈值,而这通常需要较深的领域知识或大量的实践,因此目前仍没有一种很好的设定方法。同时,序列模式的挖掘结果往往数量很大且不易理解,可用性较低。针对上述问题,提出了一种基于逻辑的频繁序列模式挖掘算法即LFSPM算法,并首次在频繁序列模式挖掘算法中引入了逻辑的思想,通过逻辑规则过滤,大大优化了结果集。实验证明,该算法较好地解决了支持度设置问题及挖掘结果可理解性不高的问题。
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