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Andreas Schmidt

Andreas Schmidt
Raum 0445 B
Universität Kassel
Fachbereich Elektrotechnik/Informatik
Fachgebiet Wissensverarbeitung
Wilhelmshöher Allee 73
34121 Kassel
Tel.: +49 561 804-6254
Fax.: +49 561 804-6259
Email:


Projects


FEE: Frühzeitige Erkennung und Entscheidungsunterstützung für kritische Situationen im Produktionsumfeld

Teaching

Supervised Theses
  • Florian Fassing: Exceptional Model Mining zur Entdeckung Abnormaler Communities
Summer Semester 2017
Winter Semester 2016/2017
Summer Semester 2016
Winter Semester 2015/2016
Summer Semester 2015


Events


2015


Publications

2017

Anomaly Analytics and Structural Assessment in Process Industries.
In: Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017). Eindhoven University of Technology, Eindhoven, The Netherlands, 2017.
Martin Atzmueller, David Arnu and Andreas Schmidt.
URL   
Anomaly Detection and Structural Analysis in Industrial Production Environments.
In: Proc. International Data Science Conference (IDSC 2017). Salzburg, Austria, 2017.
Martin Atzmueller, David Arnu and Andreas Schmidt.
URL   
HypGraphs: An Approach for Analysis and Assessment of Graph-Based and Sequential Hypotheses.
In: New Frontiers in Mining Complex Patterns. Postproceedings NFMCP 2016, series LNAI. Springer Verlag, Berlin/Heidelberg, Germany, 2017.
Martin Atzmueller, Andreas Schmidt, Benjamin Kloepper and David Arnu.
URL   

2016

Big Data Analytics for Proactive Industrial Decision Support: Approaches & First Experiences in the Context of the FEE Project.
atp edition, 58(9), 2016.
Martin Atzmueller, Benjamin Kloepper, Hassan Al Mawla, Benjamin Jäschke, Martin Hollender, Markus Graube, David Arnu, Andreas Schmidt, Sebastian Heinze, Lukas Schorer, Andreas Kroll, Gerd Stumme and Leon Urbas.
 
Big Data Analytics Using Local Exceptionality Detection.
In: Enterprise Big Data Engineering, Analytics, and Management. IGI Global, Hershey, PA, USA, 2016.
Martin Atzmueller, Dennis Mollenhauer and Andreas Schmidt.
 
DASHTrails: An Approach for Modeling and Analysis of Distribution-Adapted Sequential Hypotheses and Trails.
In: Proc. WWW 2016 (Companion). 2016.
Martin Atzmueller, Andreas Schmidt and Mark Kibanov.
URL   
HypGraphs: An Approach for Modeling and Comparing Graph-Based and Sequential Hypotheses.
In: Proc. ECML-PKDD Workshop on New Frontiers in Mining Complex Patterns (NFMCP). Riva del Garda, Italy, 2016.
Martin Atzmueller, Andreas Schmidt, Benjamin Kloepper and David Arnu.
 
Sequential Modeling and Structural Anomaly Analytics in Industrial Production Environments.
In: Proc. LWA 2016 (KDML Special Track). University of Potsdam, Potsdam, Germany, 2016.
Martin Atzmueller, Andreas Schmidt and David Arnu.
 
Data Preparation for Big Data Analytics: Methods & Experiences.
In: Enterprise Big Data Engineering, Analytics, and Management. IGI Global, Hershey, PA, USA, 2016.
Andreas Schmidt, Martin Atzmueller and Martin Hollender.
 

2015

The FEE Project: Introduction and First Insights.
In: Proc. UIS Workshop. 2015.
Andreas Schmidt, Martin Atzmueller and Gerd Stumme.
URL