Process Mining

We are are developing a two-step approach in the area of process mining using synthesis algorithms for p/t-nets:

  • First step (preprocessing): Construct an labelled prime event structure (LPES) with cutoff-list from an event log through detecting loops, causality, concurrency and noise. Since LPES with cutoff-list are a more general model than p/t-nets, causal structures can be detected with less loss of information than with approaches using directly p/t-net based models. For the handling of noise we employ statistical methods.
  • Second step (synthesis): Synthesize a Petri net from the result of the first step.

Synthese-Tool

We developed command line tool in JAVA for the synthesis of bounded p/t-nets from LPES with cutoff-list using wrong continuations. We are currently reimplementing the tool in order to improve its performance. In the meanwhile, no download is available.   

 

 

Preprocessing-Tool

We are currently working on using hypothesis tests in order to filter infrequent behavior from an event log. We developed the command line tool h0logfilter for producing a causal footprint without infrequent behavior from an event log. The footprint can be used to construct directly a process model from it or to construct an LPES with cutoff-list reflecting the causal structures detected in the log.

 

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