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Incorporating negative information to process discovery of complex systems

Author
Ponce de León, H.; Nardelli, L.; Carmona, J.; vanden Broucke, S.K.L.M.
Type of activity
Journal article
Journal
Information sciences
Date of publication
2018-01-01
Volume
422
First page
480
Last page
496
DOI
https://doi.org/10.1016/j.ins.2017.09.027 Open in new window
Repository
http://hdl.handle.net/2117/108870 Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S0020025516315444?via%3Dihub Open in new window
Abstract
The discovery of a formal process model from event logs describing real process executions is a challenging problem that has been studied from several angles. Most of the contributions consider the extraction of a model as a one-class supervised learning problem where only a set of process instances is available. Moreover, the majority of techniques cannot generate complex models, a crucial feature in some areas like manufacturing. In this paper we present a fresh look at process discovery where...
Citation
Ponce de León, H., Nardelli, L., Carmona, J., vanden Broucke, S.K.L.M. Incorporating negative information to process discovery of complex systems. "Information sciences", 1 Gener 2018, vol. 422, p. 480-496.
Keywords
Convex polyhedrons, Formal process models, Negative information, Process execution, Process instances, Prototype implementations, Satisfiability modulo theories, Supervised learning problems
Group of research
ALBCOM - Algorithms, Computational Biology, Complexity and Formal Methods

Participants

  • Ponce de León, Hernán  (author)
  • Nardelli, Lucio  (author)
  • Carmona Vargas, Jose  (author)
  • vanden Broucke, Seppe  (author)