以日历格作为框架来研究时序关联规则,提出了一个有效的挖掘算法。在用户指定的日历模式下,首先通过一次扫描产生所有的频繁2项集及相应的1*日历模式,在此基础上产生k*日历模式,并利用聚集性质产生候选K项集及相应的日历模式,最后扫描事务数据库产生所有的频繁项集及其日历模式。实验证明,该算法具有较好的性能。An efficient algorithm for temporal association rules based on calendar patterns was presented.A user-given calendar schema was adopted to specify the interesting rime intervals as calendar patterns.Then database was scanned once to find all frequent 2-itemsets and their 1-star calendar patterns.Aggregation property and Apriori property were utilized to find all candidate patterns.Finally,calendar-based temporal association rules were obtained through scanning.The experimental results indicate that this proposed algorithm is feasible and efficient.福建省自然科学基金资助项目(A0310008);; 福建省高新技术研究开放计划重点资助项目(2003H043
