关键词: 流程模型挖掘, 行为足迹, 行为矩阵, 聚类, 行为特征网, 合成

Abstract: To make event log which contained vast activities mine process model effectively,a decomposed mining method for process model based on behavior feature net was proposed.The behavior footprint between activities were found based on activity logs and achieve corresponding behavior matrix as well.The behavior relation graph of activities was computed with behavioral matrix,and the clustering of activities was generated.Sub-log was filtered by existing mining algorithm for discovering subnets,and interface places were added to each subnet to structure behavior feature nets of sub-logs.On the basis of behavior feature nets,the complete net was synthesized with viewpoint of synthetic nets,and so as to mine the process model.The effectiveness of the proposed method was verified by a simulation analysis.

Key words: process model mining, behavior footprint, behavior matrix, cluster, behavior feature net, synthesis