Author
Listed:
- Alessio Bottrighi
(Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy)
- Marco Guazzone
(Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy)
- Giorgio Leonardi
(Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy)
- Stefania Montani
(Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy)
- Manuel Striani
(Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy)
- Paolo Terenziani
(Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy)
Abstract
The traces of process executions are a strategic source of information, from which a model of the process can be mined. In our recent work, we have proposed SIM (semantic interactive miner), an innovative process mining tool to discover the process model incrementally: it supports the interaction with domain experts, who can selectively merge parts of the model to achieve compactness, generalization, and reduced redundancy. We now propose a substantial extension of SIM, making it able to exploit (both automatically and interactively) pre-encoded taxonomic knowledge about the refinement (ISA relations) and composition (part-of relations) of process activities, as is available in many domains. The extended approach allows analysts to move from a process description where activities are reported at the ground level to more user-interpretable/compact descriptions, in which sets of such activities are abstracted into the “macro-activities” subsuming them or constituted by them. An experimental evaluation based on a real-world setting (stroke management) illustrates the advantages of our approach.
Suggested Citation
Alessio Bottrighi & Marco Guazzone & Giorgio Leonardi & Stefania Montani & Manuel Striani & Paolo Terenziani, 2022.
"Integrating ISA and Part-of Domain Knowledge into Process Model Discovery,"
Future Internet, MDPI, vol. 14(12), pages 1-29, November.
Handle:
RePEc:gam:jftint:v:14:y:2022:i:12:p:357-:d:986693
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