Vergleich von Distanzen und Kernel für Klassifikatoren zur Optimierung der Annotation von Bildern. - Alexander Askinadze (BTW Workshops, 2015)

Pisco: A Computational Approach to Predict Personality Types from Java Source Code. - Matthias Liebeck; Pashutan Modaresi; Alexander Askinadze; Stefan Conrad 001 (FIRE (Working Notes), 2016)

Anwendung der Regressions-SVM zur Vorhersage studentischer Leistungen. - Alexander Askinadze (GvD, 2016)

Fake war crime image detection by reverse image search. - Alexander Askinadze (BTW (Workshops), 2017)

Application of the Dynamic Time Warping Distance for the Student Drop-out Prediction on Time Series Data. - Alexander Askinadze; Stefan Conrad 001 (EDM, 2017)

A Web Service Architecture for Tracking and Analyzing Data from Distributed E-Learning Environments. - Alexander Askinadze; Stefan Conrad 001 (WETICE, 2017)

The First Data Science Challenge at BTW 2017. - Pascal Hirmer; Tim Waizenegger; Ghareeb Falazi; Majd Abdo; Yuliya Volga; Alexander Askinadze; Matthias Liebeck; Stefan Conrad 001; Tobias Hildebrandt; Conrad Indiono; Stefanie Rinderle-Ma; Martin Grimmer 002; et al. (Datenbank-Spektrum, 2017)

Predicting Student Test Performance based on Time Series Data of eBook Reader Behavior Using the Cluster Distance Space Transformation. - Alexander Askinadze; Matthias Liebeck; Stefan Conrad 001 (ICCE, 2018)

Respecting Data Privacy in Educational Data Mining: An Approach to the Transparent Handling of Student Data and Dealing with the Resulting Missing Value Problem. - Alexander Askinadze; Stefan Conrad 001 (WETICE, 2018)

Predicting Student Dropout in Higher Education Based on Previous Exam Results. - Alexander Askinadze; Stefan Conrad 001 (EDM, 2019)