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Alexander Seeliger · Study

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Alexander Seeliger

6 works· latest 2020· 1 institutionscluster: provisionalORCID 0000-0002-0649-6225

h-index6

i106

Citations356

Works here6

16

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20

Most cited in this library

Analyzing business process anomalies using autoencoders2018 · 112 citations
BINet: Multivariate Business Process Anomaly Detection Using Deep Learning2018 · 88 citations
Unsupervised Anomaly Detection in Noisy Business Process Event Logs Using Denoising Autoencoders2016 · 61 citations
Detecting Concept Drift in Processes using Graph Metrics on Process Graphs2017 · 48 citations
ProcessExplorer: Intelligent Process Mining Guidance2019 · 24 citations

Works

6 shown

DeepAlign: Alignment-Based Process Anomaly Correction Using Recurrent Neural Networks

Lecture notes in computer science·2020·4 authors·other·Open access

23citations

ProcessExplorer: Intelligent Process Mining Guidance

Lecture notes in computer science·2019·4 authors·other

24citations

Analyzing business process anomalies using autoencoders

Machine Learning·2018·2 authors·Open access

112citations

BINet: Multivariate Business Process Anomaly Detection Using Deep Learning

Lecture notes in computer science·2018·3 authors·other

88citations

Detecting Concept Drift in Processes using Graph Metrics on Process Graphs

·2017·3 authors·other

48citations

Unsupervised Anomaly Detection in Noisy Business Process Event Logs Using Denoising Autoencoders

Lecture notes in computer science·2016·3 authors·other

61citations