Many hospital information systems nowadays record data about the executed medical process instances in the form of traces in an event log. In this paper we present a framework able to convert actions found in the traces into higher level concepts, on the basis of domain knowledge. Abstracted traces are then provided as an input to semantic process mining. The approach has been tested in stroke care, where we show how the abstraction mechanism allows the user to mine process models that are easier to interpret, since unnecessary details are hidden, but key behaviors are clearly visible.
CITATION STYLE
Montani, S., Striani, M., Quaglini, S., Cavallini, A., & Leonardi, G. (2017). Knowledge-based trace abstraction for semantic process mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10259 LNAI, pp. 267–271). Springer Verlag. https://doi.org/10.1007/978-3-319-59758-4_30
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