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Control-flow anomaly detection by process mining-based feature extraction and dimensionality reduction

Control-flow anomaly detection by process mining-based feature extraction and dimensionality reduction

17 February 2025
Francesco Vitale
Marco Pegoraro
W. V. Aalst
Nicola Mazzocca
ArXivPDFHTML

Papers citing "Control-flow anomaly detection by process mining-based feature extraction and dimensionality reduction"

12 / 12 papers shown
Title
Trace Encoding in Process Mining: a survey and benchmarking
Trace Encoding in Process Mining: a survey and benchmarking
Sylvio Barbon Junior
Paolo Ceravolo
R. Oyamada
G. Tavares
AI4TS
64
20
0
05 Jan 2023
A Survey on Explainable Anomaly Detection
A Survey on Explainable Anomaly Detection
Zhong Li
Yuxuan Zhu
M. Leeuwen
79
75
0
13 Oct 2022
Process Modeling and Conformance Checking in Healthcare: A COVID-19 Case
  Study
Process Modeling and Conformance Checking in Healthcare: A COVID-19 Case Study
Elisabetta Benevento
Marco Pegoraro
Mattia Antoniazzi
Harry H. Beyel
Viki Peeva
P. Balfanz
Wil M.P. van der Aalst
L. Martin
G. Marx
15
6
0
22 Sep 2022
ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels
ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels
Yue Zhao
Guoqing Zheng
Subhabrata Mukherjee
R. McCann
Ahmed Hassan Awadallah
NoLa
38
25
0
24 Aug 2022
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly
  Detection
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection
Yingjie Zhou
Xuchen Song
Yanru Zhang
Fanxing Liu
Ce Zhu
Lingqiao Liu
UQCV
73
103
0
22 May 2021
Recomposition vs. Prediction: A Novel Anomaly Detection for Discrete
  Events Based On Autoencoder
Recomposition vs. Prediction: A Novel Anomaly Detection for Discrete Events Based On Autoencoder
Lun-Pin Yuan
Peng Liu
Sencun Zhu
AI4TS
42
15
0
27 Dec 2020
Decision-Making with Auto-Encoding Variational Bayes
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
BDL
319
10,591
0
17 Feb 2020
DeepAlign: Alignment-based Process Anomaly Correction using Recurrent
  Neural Networks
DeepAlign: Alignment-based Process Anomaly Correction using Recurrent Neural Networks
Timo Nolle
Alexander Seeliger
Nils Thoma
M. Mühlhäuser
22
17
0
29 Nov 2019
Shapley Values of Reconstruction Errors of PCA for Explaining Anomaly
  Detection
Shapley Values of Reconstruction Errors of PCA for Explaining Anomaly Detection
Naoya Takeishi
FAtt
111
33
0
08 Sep 2019
BINet: Multi-perspective Business Process Anomaly Classification
BINet: Multi-perspective Business Process Anomaly Classification
Timo Nolle
Stefan Luettgen
Alexander Seeliger
M. Mühlhäuser
AI4TS
41
71
0
08 Feb 2019
Analyzing Business Process Anomalies Using Autoencoders
Analyzing Business Process Anomalies Using Autoencoders
Timo Nolle
Stefan Luettgen
Alexander Seeliger
M. Mühlhäuser
40
87
0
03 Mar 2018
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
863
21,815
0
22 May 2017
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