Business process analysis based on anomaly detection in event logs: a study on an incident management case

Date
2021-01-05
Authors
Rojas Krugger, Esther Maria
Maita, Ana Rocío Cárdenas
Alves, Juliana Cristina Barbosa
Fantinato, Marcelo
Marques Peres, Sarajane
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1071
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Abstract
Business processes allow anomalies to occur during execution. Anomaly detection aims to discover behaviors that are not typical or expected in the business process. In fact, early detection helps prevent intrusion and other risks in companies. There are several approaches that address this problem in process mining. This paper discusses anomaly detection approaches in business process discovery using a real-world event log from an ITIL-covered incident management process. We discuss benefits and limitations of using knowledge from process models discovered after treating anomalies.
Description
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Data, Text and Web Mining for Business Analytics, anomaly detection, autoencoders, event log analysis, process mining
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10 pages
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Proceedings of the 54th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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