Towards Process Mining with Graph Transformation Systems

This paper is about process mining with graph transformation systems (gtss). Given a set of observed transition sequences, the goal is to find a gts – that is a finite set of graph transformation rules – that models these transition sequences as well as possible. In this paper the focus is on real-word processes such as business processes or (human) problem solving strategies, with the aim of better understanding such processes. The observed behaviour is not assumed to be either complete or error-free and the given model is expected to generalize the observed behaviour and be robust to erroneous input. The paper presents some basic algorithms that obtain gtss from observed transition sequences and gives a method to compare the resulting gtss.

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