Title
Role Identification Based on the Information Dependency Complexity
Abstract
Process mining mainly focuses on the control flow perspective at present. In comparison, role-based process mining stresses the importance of roles in business processes and their interactive relationships. Though some scholars come to pay attention to role identification, their studies are not sufficient in the analysis of role complexity. In this paper, a role coupling complexity metric based on information flow in the process is proposed, and the design structure matrix DSM is used for role identification in business processes. Then, some typical process logs are mined by an improved particle swarm optimization method. As the coupling complexity between roles is increasingly reduced, our method can recognize roles with lower complexity. Finally, experiments are performed to verify the effectiveness of the method.
Year
DOI
Venue
2013
10.1007/978-3-642-53917-6_25
ADMA (2)
Keywords
DocType
Volume
dsm matrix,information complexity,particle swarm optimization,role identification
Conference
8347 LNAI
Issue
Citations 
PageRank 
PART 2
0
0.34
References 
Authors
13
3
Name
Order
Citations
PageRank
Weidong Zhao100.34
Haitao Liu25812.91
Xi Liu33610.08