Computer Science ›› 2020, Vol. 47 ›› Issue (7): 78-83.doi: 10.11896/jsjkx.190600140

• Database & Big Data & Data Science • Previous Articles     Next Articles

Mining Method of Business Process Change Based on Cost Alignment

LIU Jing, FANG Xian-wen   

  1. College of Mathematics and Big Data,Anhui University of Science and Technology,Huainan,Auhui 232001,China
  • Received:2019-06-26 Online:2020-07-15 Published:2020-07-16
  • About author:LIU Jing,born in 1995,postgraduate.Her main research interests include Petri net and change mining.
    FANG Xian-wen,born in 1975,Ph.D,professor.His main research interests include Petri net and trusted software.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China(61272153,61402011),Natural Science Foundation of Anhui Pro-vince(1508085MF111,1608085QF149),and Natural Science Foundation of Colleges and Universities in Anhui Province(KJ2016A208)

Abstract: Change mining is the core of business process management,and it is particularly important to mine the changes of business processes from the event log.Most of the existing analysis methods of change mining focus on the source model or target model.From the point of view of system log,this paper proposes a business process change mining method based on cost optimal alignment.Firstly,according to the event log,the effective high frequency morphological occurrence segment is extracted,the highest cost function value of each trace alignment is calculated,and on this basis,the optimal trace alignment is found,and then the similarity between the change log and the source log is measured to mine the change set quickly and efficiently.Finally,an example is given to show the effectiveness of the method.

Key words: Change mining, Cost function, High frequency segment, Optimal alignment, Similarity degree

CLC Number: 

  • TP391.9
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