Rafet Sifa
Rafet Sifa
Professor of Applied Machine Learning at University of Bonn and Fraunhofer IAIS
Verified email at - Homepage
Cited by
Cited by
Guns, swords and data: Clustering of player behavior in computer games in the wild
A Drachen, R Sifa, C Bauckhage, C Thurau
2012 IEEE conference on Computational Intelligence and Games (CIG), 163-170, 2012
Predicting player churn in the wild
F Hadiji, R Sifa, A Drachen, C Thurau, K Kersting, C Bauckhage
2014 ieee conference on computational intelligence and games, 1-8, 2014
Combining machine learning and simulation to a hybrid modelling approach: Current and future directions
L von Rueden, S Mayer, R Sifa, C Bauckhage, J Garcke
Advances in Intelligent Data Analysis XVIII: 18th International Symposium on …, 2020
Clustering game behavior data
C Bauckhage, A Drachen, R Sifa
IEEE Transactions on Computational Intelligence and AI in Games 7 (3), 266-278, 2014
Predicting purchase decisions in mobile free-to-play games
R Sifa, F Hadiji, J Runge, A Drachen, K Kersting, C Bauckhage
proceedings of the AAAI conference on artificial intelligence and …, 2015
How players lose interest in playing a game: An empirical study based on distributions of total playing times
C Bauckhage, K Kersting, R Sifa, C Thurau, A Drachen, A Canossa
2012 IEEE conference on computational intelligence and games (CIG), 139-146, 2012
Online-only friends, real-life friends or strangers? Differential associations with passion and social capital in video game play
R Perry, A Drachen, A Kearney, S Kriglstein, LE Nacke, R Sifa, G Wallner, ...
Computers in Human Behavior 79, 202-210, 2018
A comparison of methods for player clustering via behavioral telemetry
A Drachen, C Thurau, R Sifa, C Bauckhage
arXiv preprint arXiv:1407.3950, 2013
The playtime principle: Large-scale cross-games interest modeling
R Sifa, C Bauckhage, A Drachen
2014 IEEE conference on computational intelligence and games, 1-8, 2014
Large-scale cross-game player behavior analysis on steam
R Sifa, A Drachen, C Bauckhage
Proceedings of the AAAI Conference on Artificial Intelligence and …, 2015
Archetypal Game Recommender Systems
R Sifa, C Bauckhage, A Drachen
LWA KDML, 2014
Is reinforcement learning (not) for natural language processing: Benchmarks, baselines, and building blocks for natural language policy optimization
R Ramamurthy, P Ammanabrolu, K Brantley, J Hessel, R Sifa, ...
arXiv preprint arXiv:2210.01241, 2022
Rapid prediction of player retention in free-to-play mobile games
A Drachen, E Lundquist, Y Kung, P Rao, R Sifa, J Runge, D Klabjan
Proceedings of the AAAI Conference on Artificial Intelligence and …, 2016
Predicting player churn in destiny: A Hidden Markov models approach to predicting player departure in a major online game
M Tamassia, W Raffe, R Sifa, A Drachen, F Zambetta, M Hitchens
2016 IEEE Conference on Computational Intelligence and Games (CIG), 1-8, 2016
Profiling in games: Understanding behavior from telemetry
R Sifa, A Drachen, C Bauckhage
Social interactions in virtual worlds: An interdisciplinary perspective, 337-374, 2018
Customer lifetime value prediction in non-contractual freemium settings: Chasing high-value users using deep neural networks and SMOTE
R Sifa, J Runge, C Bauckhage, D Klapper
Behavior evolution in tomb raider underworld
R Sifa, A Drachen, C Bauckhage, C Thurau, A Canossa
2013 IEEE Conference on Computational Inteligence in Games (CIG), 1-8, 2013
Towards automated auditing with machine learning
R Sifa, A Ladi, M Pielka, R Ramamurthy, L Hillebrand, B Kirsch, D Biesner, ...
Proceedings of the ACM Symposium on Document Engineering 2019, 1-4, 2019
A QUBO Formulation of the k-Medoids Problem.
C Bauckhage, N Piatkowski, R Sifa, D Hecker, S Wrobel
LWDA, 54-63, 2019
To be or not to be... social: Incorporating simple social features in mobile game customer lifetime value predictions
A Drachen, M Pastor, A Liu, DJ Fontaine, Y Chang, J Runge, R Sifa, ...
proceedings of the australasian computer science week multiconference, 1-10, 2018
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Articles 1–20