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An evolutionary technique to approximate multiple optimal alignments

Author
Taymouri, F.; Carmona, J.
Type of activity
Presentation of work at congresses
Name of edition
16th International Conference on Business Process Management
Date of publication
2018
Presentation's date
2018-09-13
Book of congress proceedings
Business Process Management,16th International Conference, BPM 2018, Sydney, NSW, Australia, September 9-14, 2018: proceedings
First page
215
Last page
232
Publisher
Springer
DOI
https://doi.org/10.1007/978-3-319-98648-7_13 Open in new window
Project funding
Graph-based Models and Methods for Computing in the Large
Repository
http://hdl.handle.net/2117/127144 Open in new window
URL
https://link.springer.com/chapter/10.1007/978-3-319-98648-7_13 Open in new window
Abstract
The alignment of observed and modeled behavior is an essential aid for organizations, since it opens the door for root-cause analysis and enhancement of processes. The state-of-the-art technique for computing alignments has exponential time and space complexity, hindering its applicability for medium and large instances. Moreover, the fact that there may be multiple optimal alignments is perceived as a negative situation, while in reality it may provide a more comprehensive picture of the model...
Citation
Taymouri, F., Carmona, J. An evolutionary technique to approximate multiple optimal alignments. A: International Conference on Business Process Management. "Business Process Management,16th International Conference, BPM 2018, Sydney, NSW, Australia, September 9-14, 2018: proceedings". Berlín: Springer, 2018, p. 215-232.
Group of research
ALBCOM - Algorithms, Computational Biology, Complexity and Formal Methods

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