Title :
A genetic algorithm for discovering process trees
Author :
Buijs, J.C.A.M. ; van Dongen, B.F. ; van der Aalst, W.M.P.
Author_Institution :
Fac. of Math. & Comput. Sci., Eindhoven Univ. of Technol., Eindhoven, Netherlands
Abstract :
Existing process discovery approaches have problems dealing with competing quality dimensions (fitness, simplicity, generalization, and precision) and may produce anomalous process models (e.g., deadlocking models). In this paper we propose a new genetic process mining algorithm that discovers process models from event logs. The tree representation ensures the soundness of the model. Moreover, as experiments show, it is possible to balance the different quality dimensions. Our genetic process mining algorithm is the first algorithm where the search process can be guided by preferences of the user while ensuring correctness.
Keywords :
data mining; genetic algorithms; tree data structures; deadlocking model; event logs; genetic process mining algorithm; process discovery approach; process trees; quality dimension; tree representation; Analytical models; Data mining; Genetic algorithms; Genetics; Predictive models; System recovery; Unified modeling language;
Conference_Titel :
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1510-4
Electronic_ISBN :
978-1-4673-1508-1
DOI :
10.1109/CEC.2012.6256458
