Paper Info
Title
A Method for Mining Process Models With Indirect Dependencies via Petri Nets.
Abstract
Process mining aims to build the models of business processes and get valuable information according to event logs generated from enterprise information systems. There exist some indirect dependences, which refer to the relationship between discontinuous activities in business processes. However, the existing approaches cannot accurately identify such dependences from the event logs. Thus, this paper extends the alpha algorithm and proposes a new one named the alpha(TR) algorithm, which uses the association rules to describe the indirect dependences. First, an algorithm is proposed to identify the choice and loop structures in the business process. Then, the association rules are mined to describe the indirect dependences. Finally, we design an extended Petri net to formalize the process model, which can accurately describe the indirect dependences. The effectiveness of the proposed approach is illustrated by the experiments on ProM.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2923624
IEEE ACCESS
Keywords
Field
DocType
Process mining,process model,indirect dependency,association rule,Petri net
Data mining,Petri net,Business process,Computer science,Process modeling,Enterprise information system,Association rule learning,Distributed computing,Process mining
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Huiming Sun100.34
YuYue Du226825.87
Liang Qi315627.14
Zhaoyang He411.37