基于时间段的时序规则发现

Mining association rules in interval-based temporal sequences

提出了一个新的基于时间段的频繁闭模式的挖掘算法,采用时间段的概念,利用频繁闭模式的特点,生成相应的时序规则。算法通过使用闭模式的性质进行剪枝优化,不生成冗余的候选序列,降低了时序规则发现的时间与空间复杂度,提高了效率。

A new algorithm was proposed to find association rules in interval-based sequences, which was based on the concept of interval time series and used the properties of frequent closed patterns. By the properties of frequent closed patterns, the algorithm can avoid generating the redundancy candidate sequences, thus decreases the time and space complexity and improves the efficiency of the algorithm.