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blogs:pub2005:genetic_process_mining [2009/05/25 12:24] (current)
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 +====== Genetic Process Mining ======
  
 +W.M.P. van der Aalst, A.K. Alves de Medeiros and A.J.M.M. Weijters\\
 +//26th International Conference on Applications and Theory of Petri Nets (ICATPN 2005), G. Ciardo and P. Darondeau, LNCS 3536, pages 48-69, 2005//\\
 +© Springer-Verlag Berling Heidelberg 2005\\
 +
 +===== Abstract =====
 +
 +The topic of process mining has attracted the attention of
 +both researchers and tool vendors in the Business Process Management
 +(BPM) space. The goal of process mining is to discover process models
 +from event logs, i.e., events logged by some information system are used
 +to extract information about activities and their causal relations. Several
 +algorithms have been proposed for process mining. Many of these algorithms
 +cannot deal with concurrency. Other typical problems are the
 +presence of duplicate activities, hidden activities, non-free-choice constructs,
 +etc. In addition, real-life logs contain noise (e.g., exceptions or
 +incorrectly logged events) and are typically incomplete (i.e., the event
 +logs contain only a fragment of all possible behaviors). To tackle these
 +problems we propose a completely new approach based on genetic algorithms.
 +As can be expected, a genetic approach is able to deal with
 +noise and incompleteness. However, it is not easy to represent processes
 +properly in a genetic setting. In this paper, we show a genetic process
 +mining approach using the so-called causal matrix as a representation
 +for individuals. We elaborate on the relation between Petri nets and this
 +representation and show that genetic algorithms can be used to discover
 +Petri net models from event logs.
 +
 +===== Links =====
 +
 +{{publications:​Aalst2005d.pdf|Download PDF}} (313 KB)