American Psychological Association 6th edition

Paprotny, A., & Theß, M. [ca. 2013]. Realtime Data Mining : Self-Learning Techniques for Recommendation Engines. In Applied and Numerical Harmonic Analysis (1 st ed. 2013) [Cd]. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-01321-3

ISO-690 (author-date, English)

PAPROTNY, Alexander und THESS, Michael, 2013. Realtime Data Mining : Self-Learning Techniques for Recommendation Engines. 1 st ed. 2013. Cham: Springer International Publishing. ISBN 9783319013213.

Modern Language Association 9th edition

Paprotny, A., und M. Theß. „Realtime Data Mining : Self-Learning Techniques for Recommendation Engines“. Applied and Numerical Harmonic Analysis, 1 st ed. 2013, cd, Springer International Publishing, 2013, https://doi.org/10.1007/978-3-319-01321-3.

Mohr Siebeck - Recht (Deutsch - Österreich)

Paprotny, Alexander/Theß, Michael: Realtime Data Mining : Self-Learning Techniques for Recommendation Engines, 1 st ed. 2013. Aufl. Cham 2013.

Emerald - Harvard

Paprotny, A. und Theß, M. (2013), Realtime Data Mining : Self-Learning Techniques for Recommendation Engines, Applied and Numerical Harmonic Analysis, 1 st ed. 2013., Bd. , Springer International Publishing, Cham, verfügbar unter:https://doi.org/10.1007/978-3-319-01321-3.

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.