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
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;
Conference_Titel :
Control Systems and Computer Science (CSCS), 2013 19th International Conference on
Conference_Location :
Bucharest
Print_ISBN :
978-1-4673-6140-8
DOI :
10.1109/CSCS.2013.19
