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Michael Platzer
Michael Platzer
Verified email at s.wu.ac.at
Title
Cited by
Cited by
Year
Ticking Away the Moments: Timing Regularity Helps to Better Predict Customer Activity
M Platzer, T Reutterer
Marketing Science 35 (5), 779-799, 2016
982016
Leveraging purchase regularity for predicting customer behavior the easy way
T Reutterer, M Platzer, N Schröder
International Journal of Research in Marketing 38 (1), 194-215, 2021
202021
Holdout-based empirical assessment of mixed-type synthetic data
M Platzer, T Reutterer
Frontiers in big Data, 43, 2021
182021
A deep recurrent neural network approach to learn sequence similarities for user-identification
S Vamosi, T Reutterer, M Platzer
Decision Support Systems 155, 113718, 2022
162022
Stochastic Models of Noncontractual Consumer Relationships
M Platzer
Vienna University of Business and Economics, 2008
102008
Customer Base Analysis with Recurrent Neural Networks
J Valendin, T Reutterer, M Platzer, K Kalcher
International Journal of Research in Marketing, 2022
92022
Customer Base Analysis with BTYDplus
M Platzer
42016
AI-based Re-identification of Behavioral Clickstream Data
S Vamosi, M Platzer, T Reutterer
arXiv preprint arXiv:2201.10351, 2022
32022
Holdout-Based Fidelity and Privacy Assessment of Mixed-Type Synthetic Data
M Platzer, T Reutterer
arXiv preprint arXiv:2104.00635, 2021
32021
AI-Based Privacy Preserving Census (like) Data Publication
J Gussenbauer, A Kowarik, K Kalcher, M Platzer
22021
Market Response Models
M Platzer
Technical University of Vienna, 2002
12002
Rule-adhering synthetic data--the lingua franca of learning
M Platzer, I Krchova
arXiv preprint arXiv:2209.06679, 2022
2022
Synthesizing Mobility Traces
K Kalcher, M Platzer, D Soukup
US Patent App. 17/449,993, 2022
2022
Special Session:“Marketing Analytics and Privacy”
R Laub, PK Kannan, M Platzer
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Articles 1–14