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