Abstract
The automated comparison of process models has received increasing attention in the last decade, due to the growing existence of process models and repositories, and the consequent need to assess similarities between the underlying processes. Current techniques for process model comparison are either structural (based on graph edit distances), or behavioural (through activity profiles or the analysis of the execution semantics). Accordingly, there is a gap between the quality of the information provided by these two families, i.e., structural techniques may be fast but inaccurate, whilst behavioural are accurate but complex. In this paper we present a novel technique, that is based on a well-known technique to compare labeled trees through the notion of Cophenetic distance. The technique lays between the two families of methods for comparing a process model: it has an structural nature, but can provide accurate information on the differences/similarities of two process models. The experimental evaluation on various benchmarks sets are reported, that position the proposed technique as a valuable tool for process model comparison.
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Notes
- 1.
We assume the problem of dealing with real activity labels, e.g., when the name of an activity in the models does not perfectly match, is resolved prior to the techniques of this paper.
- 2.
We used Discover a Process Tree using Inductive Miner (ProM 6.5) and then converted them to Petri Nets.
- 3.
The most common sequence of commands in the dataset is svn-options, svn update, svn -options indicating they use an IDE that overwrites the SVN options just to perform an update and then returns to its previous status.
- 4.
Following the semantics of block-structured models in [4], only exclusive ORs are modeled.
- 5.
Here a strict subtree of T is any subtree that does not contain the root of T.
- 6.
In all three cases, the Pearson correlation coefficient is above 0.85 with a p-value, for testing non-correlation, below \(10^{-12}\).
- 7.
Remember that the scale of metrics \(d_{\varphi }\), \(d_{ES}\) and \(d_{GED}\) is different, a fact that explains the differences on the absolute values provided in each one.
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Acknowledgements
This work is funded by Secretaria de Universitats i Recerca of Generalitat de Catalunya, under the Industrial Doctorate Program 2013DI062, and European Commission’s 7th Framework Programme project LeanBigData (Agreement 619606), and the Spanish Ministry for Economy and Competitiveness, the European Union (FEDER funds) under grant COMMAS (ref. TIN2013-46181-C2-1-R).
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Sánchez-Charles, D., Muntés-Mulero, V., Carmona, J., Solé, M. (2016). Process Model Comparison Based on Cophenetic Distance. In: La Rosa, M., Loos, P., Pastor, O. (eds) Business Process Management Forum. BPM 2016. Lecture Notes in Business Information Processing, vol 260. Springer, Cham. https://doi.org/10.1007/978-3-319-45468-9_9
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