Hierarchical conformance checking of process models based on event logs
Process mining techniques aim to extract knowledge from event logs. Conformance checking is one of the hard problems in process mining: it aims to diagnose and quantify the mismatch between observed and modeled behavior. Precise conformance checking implies solving complex optimization problems and...
| Autores: | , , |
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| Tipo de recurso: | informe técnico |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/99402 |
| Acceso en línea: | https://hdl.handle.net/2117/99402 |
| Access Level: | acceso abierto |
| Palabra clave: | Process mining Conformance checking Process diagnosis Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica |
| Sumario: | Process mining techniques aim to extract knowledge from event logs. Conformance checking is one of the hard problems in process mining: it aims to diagnose and quantify the mismatch between observed and modeled behavior. Precise conformance checking implies solving complex optimization problems and is therefore computationally challenging for real-life event logs. In this paper a technique to apply hierarchical conformance checking is presented, based on a state-of-the-art algorithm for deriving the subprocesses structure underlying a process model. Hierarchical conformance checking allows us to decompose problems that would otherwise be intractable. Moreover, users can navigate through conformance results and zoom into parts of the model that have a poor conformance. The technique has been implemented as a ProM plugin and an experimental evaluation showing the signicance of the approach is provided. |
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