DocumentCode
625204
Title
Process Discovery Using Ant Colony Optimization
Author
Chinces, Diana ; Salomie, Ioan
Author_Institution
Distrib. Syst. Lab., Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania
fYear
2013
fDate
29-31 May 2013
Firstpage
448
Lastpage
454
Abstract
This paper proposes ACO BP Miner, a novel method used to discover business process models from event logs using an Ant Colony Optimization (ACO) algorithm. ACO concepts are mapped to process model elements for enabling artificial ants to discover business process models that correctly correspond to the event logs. The process model discovered by ACO BP Miner is represented as a BPMN diagram [12]. The results are presented as a side by side comparison between the ACO BP Miner and the Genetic Miner [10].
Keywords
ant colony optimisation; business process re-engineering; data mining; ACO BP Miner; ACO algorithm; BPMN diagram; ant colony optimization; business process mining; business process model; event log; genetic miner; process discovery; Ant colony optimization; Approximation algorithms; Data mining; Genetics; Organizations; Process control; BPMN; Genetic Miner; ant colony optimization; artificial ant; business process discovery; business process mining; event logs;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Systems and Computer Science (CSCS), 2013 19th International Conference on
Conference_Location
Bucharest
Print_ISBN
978-1-4673-6140-8
Type
conf
DOI
10.1109/CSCS.2013.19
Filename
6569304
Link To Document