The Knowledge Discovery Machine Learning (KDML) group focuses on the neighboring subfields of computer science known as knowledge discovery in databases (KDD, sometimes referred to simply as data mining) and machine learning (ML). For us, these fields include on the one hand the automated analysis of large data sets using intelligent algorithms that are capable of extracting from the collected data hidden knowledge in order to produce models that can be used for prediction and decision making. On the other hand, they also include algorithms and systems that are capable of learning from experience and adapting to their environment or their users.
P. Bitzer, F. Weiß, und J. Leimeister. Eighth International Conference on Design Science Research in Information Systems and Technology (DESRIST), Helsinki, Finland (accepted for publication), (2013)
D. Krompass, M. Nickel, und V. Tresp. International Conference on Data Science and Advanced Analytics, DSAA 2014, Shanghai, China, October 30 - November 1, 2014, Seite 18--24. IEEE, (2014)
A. Coates, H. Lee, und A. Ng. Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, Volume 15 von JMLR Workshop and Conference Proceedings, Seite 215--223. JMLR W&CP, (2011)