【摘要】 <正> 如何从海量序列数据集中挖掘出序列关联(Sequential Associations)是当今科学计算和商业数据挖掘领域中一个十分重要的研究课题。人类社会的日益电子化使数据集的数量、种类和规模都在不断增大,数据集的增大导致传统挖掘算法挖掘出的序列关联大规模增多,因而如何从大量候选集中挖掘出有效序列关联面临着新的挑战。序列输入数据固有的特性、期望序列关联相关的时间约束(timing constraints)和海更多还原

【Abstract】 Ming sequential associations is becoming increasing essential in many scientific and commercial domains . Developing parallel algorithm becomes quite challenging depending on enormous size of available dataset and possibly large number of mined associations,the nature of input data and the timing constraints imposed on the desired associations. In this pape,we discuss several different parallel algorithms that cater to various situations to speed up the current mining process.更多还原