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