@inproceedings{b7cad2a000c94fed878628bbf1643832,
title = "Business process analysis based on anomaly detection in event logs: A study on an incident management case",
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.",
author = "Krugger, \{Esther M.R.\} and Maita, \{Ana R.C.\} and Alves, \{Juliana C.B.\} and Marcelo Fantinato and Peres, \{Sarajane M.\}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE Computer Society. All rights reserved.; 54th Annual Hawaii International Conference on System Sciences, HICSS 2021 ; Conference date: 04-01-2021 Through 08-01-2021",
year = "2021",
language = "English",
series = "Proceedings of the Annual Hawaii International Conference on System Sciences",
publisher = "IEEE Computer Society",
pages = "1071--1080",
editor = "Bui, \{Tung X.\}",
booktitle = "Proceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021",
}