Process Mining Based on Statistic Ordering Relations of Events
An explicit process model is vital in business processes.However,it is complicated and time consuming to create a workflow design.Also discords usually occur between the perceived management processes and the actual workflow processes.Under this condition,the process discovery techniques emerge.The aim is to rebuild a workflow model (e.g.a Petri net) of a business process based on the execution log.The model should give an abstract representation of the system and reproduce the log.This model can be further applied for process redesign/improvement and performance/reliability evaluation.In this paper,we present a new algorithm derived from α algorithm for process discovery in term of Petri nets,where statistic long distance causal relationship is taken into consideration.Also this algorithm covers some shortages in a-algorithm.
process mining workflow mining statistical casual relationship Petri nets
Zhou Huan Lin Chuang Deng Yiping
Department of Computer Sdence and Technology University of Tsinghua,Beijing,China,100084
国际会议
郑州
英文
1846-1853
2013-10-19（万方平台首次上网日期，不代表论文的发表时间）