no code implementations • 3 May 2017 • Niek Tax, Xixi Lu, Natalia Sidorova, Dirk Fahland, Wil M. P. van der Aalst
In process mining, precision measures are used to quantify how much a process model overapproximates the behavior seen in an event log.
no code implementations • 3 Apr 2019 • Seyed Amin Tabatabaei, Xixi Lu, Mark Hoogendoorn, Hajo A. Reijers
In this paper we propose an approach that is able to find groups of patients based on a small sample of positive examples given by a domain expert.
1 code implementation • 16 Oct 2020 • Xixi Lu, Avigdor Gal, Hajo A. Reijers
In this paper, we propose FlexHMiner, a three-step approach to discover processes with multi-level interleaved subprocesses.
1 code implementation • 17 Mar 2022 • Suhwan Lee, Xixi Lu, Hajo A. Reijers
We compare these predictive anomaly detection methods to four classical unsupervised anomaly detection approaches (such as Isolation forest and LOF) in the online setting.
1 code implementation • 28 Mar 2023 • Olusanmi Hundogan, Xixi Lu, Yupei Du, Hajo A. Reijers
Current methods to generate counterfactual sequences either do not take the process behavior into account, leading to generating invalid or infeasible counterfactual process instances, or heavily rely on domain knowledge.
1 code implementation • 28 Aug 2023 • Mozhgan Vazifehdoostirani, Laura Genga, Xixi Lu, Rob Verhoeven, Hanneke van Laarhoven, Remco Dijkman
Process pattern discovery methods (PPDMs) aim at identifying patterns of interest to users.
no code implementations • 2 Oct 2023 • Bart J. Verhoef, Xixi Lu
The goal was to find optimal policies for staff members when clients are displaying any type of aggressive behavior.
1 code implementation • 13 Oct 2023 • Suhwan Lee, Marco Comuzzi, Xixi Lu, Hajo A. Reijers
This paper proposes an evaluation framework for assessing the stability of models for online predictive process monitoring.