KNOWLEDGE MANAGEMENT

AND DISCOVERY LAB

KMD stands for "Knowledge Management and Discovery" .

The KMD Lab is part of the department Technical and Business Information Systems (ITI) .

The KMD Lab has been established in February 2003.

In the KMD lab, we develop and apply data mining methods for dynamic environments, with particular emphasis on:

• Machine Learning methods for streams and time series with gaps – prediction and feature contribution
• Parsimonious usage of data and features – cost-aware active feature acquisition methods
• Design of human-understandable solutions

Our application areas are:

• Medical Mining I: Treatment prediction, phenotyping in medical research
• Medical Mining II: Human interaction with mHealth apps
• Experiments I: Analysis of participant behaviour in experimental settings
• Experiments II: Experiment design and analysis of human behaviour in human-machine interaction

More on our research can be found here.

Our research is reflected in our teaching curriculum, which is built around the topic of data mining: Students learn underpinnings of data mining in all bachelor courses we offer. In the mandatory courses ITO and WMS of the Bachelor Wirtschaftsinformatik degree, we focus on mining for business applications. In the Recommenders course, we elaborate on the mining methods for static and stream recommenders.

In the courses Data Mining I (two variants, one for bachelor degrees, one for master degrees), students learn fundamentals on algorithms, model evaluation and data preparation. In Data Mining II, students learn learning methods for timestamped data. In the seminars, team projects and individual projects, students learn to design and apply mining and machine learning methods in realistic applications, and they get involved in our research - in team projects and individual projects. Our courses can be found under Study.

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