计算机科学 ›› 2019, Vol. 46 ›› Issue (12): 334-340.doi: 10.11896/jsjkx.180901654
• 交叉与前沿 • 上一篇
宋健, 方贤文, 王丽丽, 刘祥伟
SONG Jian, FANG Xian-wen, WANG Li-li, LIU Xiang-wei
摘要： 在业务流程优化过程中,从非频繁行为中挖掘隐变迁是重要任务之一。从非频繁行为中挖掘隐变迁,能够更好地还原流程模型,提高流程的运行效率。文中依据行为轮廓的理论,在频率较高的日志中进行挖掘以获得初始模型。首先利用合理性阈值对事件日志进行过滤,得到有效的低频序列日志;其次利用低频序列日志优化初始模型,通过对各活动间行为轮廓关系与源模型的对比,来找到变化的区域,将可能存在的隐变迁挖掘出来;然后通过优化指标对挖掘到的隐变迁进行进一步验证,从而得到完整的含隐变迁的过程模型;最后通过具体的事例以及仿真对所构建的模型进行分析,并验证该方法的有效性。
中图分类号:
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