Computer Science ›› 2019, Vol. 46 ›› Issue (2): 321-326.doi: 10.11896/j.issn.1002-137X.2019.02.049

• Interdiscipline & Frontier • Previous Articles     Next Articles

Analysis of Effective Low-frequency Behavioral Patterns Based on Petri Net Behavior Closeness

HAO Hui-jing, FANG Xian-wen, WANG Li-li, LIU Xiang-wei   

  1. College of Mathematics and Big Data,Anhui University of Science and Technology,Huainan,Anhui 232001,China
  • Received:2018-01-17 Online:2019-02-25 Published:2019-02-25

Abstract: Low-frequency behavior pattern analysis is one of the important contents of process management.It is very important to distinguish low-frequency logs and noise logs effectively in business process mining.At present,most of the researches have dealt with the direct filtering of low-frequency behavior in the process model as noise,but some low frequency behavior are valid for the model.This paper presented an effective low-frequency pattern analysis method based on Petri nets’ behavioral closeness.Firstly,a reasonable process model is established according to the given event log.Then,all low-frequency log sequences in the process model are found by iteratively expanding the initial patterns.Based on this,the behavioral distance vectors of the log and the model are calculated,and thebehavior closenessof log and model is used to find the effective low-frequency behavioral pattern.Finally,an example is given to verify the feasibility of this method.

Key words: Behavior closeness, Event log, Low frequency patterns, Threshold

CLC Number: 

  • TP391.9
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