DocumentCode :
1911367
Title :
Business process mining algorithms
Author :
Chinces, Diana ; Salomie, Ioan
Author_Institution :
Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania
fYear :
2013
fDate :
5-7 Sept. 2013
Firstpage :
271
Lastpage :
277
Abstract :
This paper presents our work in developing three business process mining algorithms, followed by a comparison between GLS Miner, ILS Miner and ACO Miner. All of these algorithms have been proved as generating better solutions compared to the state of the art and can discover process models that correctly map to the event log. The algorithms and a comparison between them is presented in the current paper, as well as the mapping of each algorithm to the common business process structures.
Keywords :
ant colony optimisation; business data processing; data mining; workflow management software; ant colony optimization; business process mining algorithms; business process structures; event log; process models; workflow management systems; Computational modeling; Heuristic algorithms; Optimization; Organizations; PROM; Search problems; ACO BP Miner; Ant Colony Optimization; BPMN; GLS Miner; Guided Local Search; ILS Miner; Iterative Local Search; business process mining; event log;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computer Communication and Processing (ICCP), 2013 IEEE International Conference on
Conference_Location :
Cluj-Napoca
Print_ISBN :
978-1-4799-1493-7
Type :
conf
DOI :
10.1109/ICCP.2013.6646120
Filename :
6646120
Link To Document :
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