DocumentCode :
1980674
Title :
Improving genetic process mining using Honey Bee algorithm
Author :
Seleem, Yahia Z. ; Mohamed, Marghny H. ; Hussain, Khaled F.
Author_Institution :
Dept. of Inf. Syst., Assiut Univ., Assiut, Egypt
fYear :
2013
fDate :
23-25 Sept. 2013
Firstpage :
59
Lastpage :
65
Abstract :
Process mining refers to the extraction of process models from event logs. This paper presents a new process mining approach based on the combination of Honey Bee algorithm and Genetic Algorithm in which the benefits of Honey Bee algorithm is used where the concept of neighborhood search for a solution emerges from intelligent behavior of honeybee and the diversity of Genetic algorithm to find the global optimum. The new process mining approach presented in this paper is implemented as a plug-in in the process mining framework http://www.processmining.org. Computational experiments show that the process mining approach present in this paper gives a significant improvement over the basic Genetic algorithm.
Keywords :
data mining; genetic algorithms; search problems; event logs; genetic algorithm; genetic process mining; honey bee algorithm; neighborhood search; process models extraction; Classification algorithms; Clustering algorithms; Data mining; Genetic algorithms; Genetics; Sociology; Statistics; Data mining; Genetic Algorithm; Honey Bee Algorithm; Petri nets; Process Mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Informatics and Applications (ICIA),2013 Second International Conference on
Conference_Location :
Lodz
Print_ISBN :
978-1-4673-5255-0
Type :
conf
DOI :
10.1109/ICoIA.2013.6650230
Filename :
6650230
Link To Document :
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