Skip to Main content Skip to Navigation
Conference papers

Using Domain Knowledge to Enhance Process Mining Results

Abstract : Process discovery algorithms typically aim at discovering process models from event logs. Most algorithms achieve this by solely using an event log, without allowing the domain expert to influence the discovery in any way. However, the user may have certain domain expertise which should be exploited to create better process models. In this paper, we address this issue of incorporating domain knowledge to improve the discovered process model. First, we present a verification algorithm to verify the presence of certain constraints in a process model. Then, we present three modification algorithms to modify the process model. The outcome of our approach is a Pareto front of process models based on the constraints specified by the domain expert and common quality dimensions of process mining.
Document type :
Conference papers
Complete list of metadata

Cited literature [24 references]  Display  Hide  Download

https://hal.inria.fr/hal-01651892
Contributor : Hal Ifip <>
Submitted on : Wednesday, November 29, 2017 - 4:06:52 PM
Last modification on : Wednesday, November 29, 2017 - 4:34:49 PM

File

440701_1_En_4_Chapter.pdf
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

P. Dixit, J. Buijs, Wil Aalst, B. Hompes, J. Buurman. Using Domain Knowledge to Enhance Process Mining Results. 5th International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA), Dec 2015, Vienna, Austria. pp.76-104, ⟨10.1007/978-3-319-53435-0_4⟩. ⟨hal-01651892⟩

Share

Metrics

Record views

119

Files downloads

87