Many information systems nowadays record data about the process instances executed at the organization in the form of traces in a 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 the medical domain of 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.

Towards semantic process mining through knowledge-based trace abstraction

G. Leonardi;S. Quaglini;S. Montani
2019-01-01

Abstract

Many information systems nowadays record data about the process instances executed at the organization in the form of traces in a 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 the medical domain of 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.
2019
Lecture Notes in Business Information Processing
Inglese
7th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2017
2017
che
340
45
64
20
978-3-030-11637-8
978-3-030-11638-5
Springer Verlag
Knowledge-based trace abstraction; Medical applications; Semantic process mining
no
none
Leonardi, G.; Striani, M.; Quaglini, S.; Cavallini &, A.; Montani, S.
273
info:eu-repo/semantics/conferenceObject
5
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1551965
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