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Peter Fettke
Peter Fettke
DFKI, Saarland University
Verified email at dfki.de - Homepage
Title
Cited by
Cited by
Year
Industry 4.0
H Lasi, P Fettke, HG Kemper, T Feld, M Hoffmann
Business & information systems engineering 6, 239-242, 2014
63412014
State-of-the-Art des State-of-the-Art
P Fettke
Wirtschaftsinformatik 48 (4), 257-266, 2006
4762006
Predicting process behaviour using deep learning
J Evermann, JR Rehse, P Fettke
Decision Support Systems, 2017
4372017
Empirical research in business process management–analysis of an emerging field of research
C Houy, P Fettke, P Loos
Business Process Management Journal 16 (4), 619-661, 2010
3912010
Classification of reference models: a methodology and its application
P Fettke, P Loos
Information systems and e-business management 1, 35-53, 2003
3902003
Industrie 4.0
H Lasi, P Fettke, HG Kemper, T Feld, M Hoffmann
Wirtschaftsinformatik 56, 261-264, 2014
3052014
Referenzmodellierungsforschung
P Fettke, P Loos
Wirtschaftsinformatik 5 (46), 331-340, 2004
2952004
Perspectives on reference modeling
P Fettke, P Loos
Reference modeling for business systems analysis, 1-21, 2007
288*2007
Business process reference models: Survey and classification
P Fettke, P Loos, J Zwicker
International Conference on Business Process Management, 469-483, 2005
2582005
How conceptual modeling is used
P Fettke
Communications of the Association for Information Systems 25 (1), 43, 2009
1802009
A deep learning approach for predicting process behaviour at runtime
J Evermann, JR Rehse, P Fettke
Business Process Management Workshops: BPM 2016 International Workshops, Rio …, 2017
1502017
A systematic literature review on state-of-the-art deep learning methods for process prediction
DA Neu, J Lahann, P Fettke
Artificial Intelligence Review 55 (2), 801-827, 2022
1432022
Time series classification using deep learning for process planning: A case from the process industry
N Mehdiyev, J Lahann, A Emrich, D Enke, P Fettke, P Loos
Procedia Computer Science 114, 242-249, 2017
1432017
Ontological evaluation of reference models using the Bunge-Wand-Weber model
P Fettke, P Loos
AMCIS 2003 Proceedings, 384, 2003
1392003
Towards an integrative big data analysis framework for data-driven risk management in industry 4.0
T Niesen, C Houy, P Fettke, P Loos
2016 49th Hawaii international conference on system sciences (HICSS), 5065-5074, 2016
1342016
Evaluating forecasting methods by considering different accuracy measures
N Mehdiyev, D Enke, P Fettke, P Loos
Procedia Computer Science 95, 264-271, 2016
1082016
The Process Model Matching Contest 2013
U Cayoglu, R Dijkman, M Dumas, P Fettke, L Garcıa-Banuelos, P Hake, ...
4th International Workshop on Process Model Collections: Management and …, 2013
106*2013
Multiperspective evaluation of reference models–towards a framework
P Fettke, P Loos
International Conference on Conceptual Modeling, 80-91, 2003
1002003
A novel business process prediction model using a deep learning method
N Mehdiyev, J Evermann, P Fettke
Business & information systems engineering 62, 143-157, 2020
992020
The Research Field “Modeling Business Information Systems” Current Challenges and Elements of a Future Research Agenda
U Frank, S Strecker, P Fettke, J Vom Brocke, J Becker, E Sinz
Wirtschaftsinformatik 56, 49-54, 2014
97*2014
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