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Applying Inductive Logic Programming to Process Mining

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Inductive Logic Programming (ILP 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4894))

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Abstract

The management of business processes has recently received a lot of attention. One of the most interesting problems is the description of a process model in a language that allows the checking of the compliance of a process execution (or trace) to the model. In this paper we propose a language for the representation of process models that is inspired to the SCIFF language and is an extension of clausal logic. A process model is represented in the language as a set of integrity constraints that allow conjunctive formulas as disjuncts in the head. We present an approach for inducing these models from data: we define a subsumption relation for the integrity constraints, we define a refinement operator and we adapt the algorithm ICL to the problem of learning such formulas. The system has been applied to the problem of inducing the model of a sealed bid auction and of the NetBill protocol. The data used for learning and testing were randomly generated from correct models of the processes.

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Hendrik Blockeel Jan Ramon Jude Shavlik Prasad Tadepalli

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Lamma, E., Mello, P., Riguzzi, F., Storari, S. (2008). Applying Inductive Logic Programming to Process Mining. In: Blockeel, H., Ramon, J., Shavlik, J., Tadepalli, P. (eds) Inductive Logic Programming. ILP 2007. Lecture Notes in Computer Science(), vol 4894. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78469-2_16

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  • DOI: https://doi.org/10.1007/978-3-540-78469-2_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78468-5

  • Online ISBN: 978-3-540-78469-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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