DocumentCode :
3640962
Title :
A framework for comparing process mining algorithms
Author :
Philip Weber;Behzad Bordbar;Peter Tiňo;Basim Majeed
Author_Institution :
School of Computer Science University of Birmingham, B15 2TT, UK
fYear :
2011
Firstpage :
625
Lastpage :
628
Abstract :
There are many process mining algorithms with different theoretical foundations and aims, raising the question of how to choose the best for a particular situation. A framework is proposed for objectively comparing algorithms for process discovery against a known ground truth, with an implementation using existing tools. Results from an experimental evaluation of five algorithms against basic process structures confirm the validity of the approach. In general, numbers of traces for mining are predictable from the structure and probabilities in the model, but there are some algorithm-specific differences.
Keywords :
"Data mining","Business","PROM","Prediction algorithms","Algorithm design and analysis","Data models","Predictive models"
Publisher :
ieee
Conference_Titel :
GCC Conference and Exhibition (GCC), 2011 IEEE
Print_ISBN :
978-1-61284-118-2
Type :
conf
DOI :
10.1109/IEEEGCC.2011.5752616
Filename :
5752616
Link To Document :
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