Novelty detection refers to the task of finding observations that are new or unusual when compared to the ‘known’ behavior. Its practical and challenging nature has been proven in many application domains while in process mining field has very limited researched. In this paper we propose a framework for the multi-modal analysis of novel behavior in business processes. The framework exploits the potential of representation learning, and allows to look at the process from different perspectives besides that of the control flow. Experiments on a real-world dataset confirm the quality of our proposal.

A Framework for the Multi-modal Analysis of Novel Behavior in Business Processes

Rullo A.
Methodology
;
Guzzo A.
Supervision
;
Tirrito E.
Software
2020

Abstract

Novelty detection refers to the task of finding observations that are new or unusual when compared to the ‘known’ behavior. Its practical and challenging nature has been proven in many application domains while in process mining field has very limited researched. In this paper we propose a framework for the multi-modal analysis of novel behavior in business processes. The framework exploits the potential of representation learning, and allows to look at the process from different perspectives besides that of the control flow. Experiments on a real-world dataset confirm the quality of our proposal.
978-3-030-62361-6
978-3-030-62362-3
Multi-modality
Novelty detection
Process mining
Trace embedding
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/315614
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