Integrating ISA and Part-of Domain Knowledge into Process Model Discovery

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 wi...

Full description

Saved in:
Bibliographic Details
Published inFuture internet Vol. 14; no. 12; p. 357
Main Authors Bottrighi, Alessio, Guazzone, Marco, Leonardi, Giorgio, Montani, Stefania, Striani, Manuel, Terenziani, Paolo
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.12.2022
Subjects
Online AccessGet full text
ISSN1999-5903
1999-5903
DOI10.3390/fi14120357

Cover

More Information
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1999-5903
1999-5903
DOI:10.3390/fi14120357