Knowledge Management & Discovery Lab

Logo Knowledge Management & 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:

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.


 

News

Test of Time Award for publication of Myra Spiliopoulou at the INFORMS Journal on Computing

15.07.2021 -

The Test of Time Award for papers published in the INFORMS Journal on Computing in the years 2000–2004 was awarded to
A Framework for the Evaluation of Session Reconstruction Heuristics in Web-Usage Analysis by Myra Spiliopoulou, Bamshad Mobasher, Bettina Berendt, and Miki Nakagawa; this paper appeared in the INFORMS Journal on Computing 15(2):171–190

https://doi.org/10.1287/ijoc.15.2.171.14445

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Screenshot_2021-08-10_10-08-54

 

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Four papers accepted at IEEE CBMS 2021

07.06.2021 -

We are pleased to announce that our four papers have been accepted for the IEEE CBMS International Symposium on Computer-Based Medical Systems, 07-09 June 2021.

Congratulations to all authors, and especially to the data science
Master DKE students Saijal Shahania for her first paper and Yash Shah
for his third one with the KMD group.

 

Circadian Conditional Granger Causalities on Ecological Momentary Assessment Data from an mHealth App by Noor Jamaludeen, Vishnu Unnikrishnan, Ruediger Pryss, Johannes Schobel, Winfried Schlee and Myra Spiliopoulou

Juxtaposing 5G Coronavirus Tweets With General Coronavirus Tweets During the Early Months of Coronavirus Outbreak by Rafi Trad and Myra Spiliopoulou

Love thy Neighbours: A Framework for Error-Driven Discovery of Useful Neighbourhoods for One-Step Forecasts on EMA data by Vishnu Unnikrishnan, Yash Shah, Miro Schleicher, Carlos Fernandez-Viadero, Mirela Strandzheva, Doroteya Velikova, Plamen Dimitrov, Rüdiger Pryss, Johannes Schobel, Winfried Schlee and Myra Spiliopoulou

User-centric vs whole-stream learning for EMA prediction by Saijal Shahania, Vishnu Unnikrishnan, Rüdiger Pryss, Robin Kraft, Johannes Schobel, Ronny Hannemann, Winfried Schlee and Myra Spiliopoulou

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Women in Data Science (WiDS) Regensburg - Virtual Conference

04.03.2021 -

Noor Jamaludeen, Clara Puga and Anne Rother will participate in the virtual conference Women in Data Science (WiDS) Regensburg (13.+14.04.2021).

We will present the following topics:

"A Comparison of Model-Based Methods for Imputing Incomplete Multivariate Time Series" (Noor Jamaludeen)

"Data Science applied to Medical Research" (Clara Puga)

"Triplet-based-learning with the help of crowdlabeling on medical data" (Anne Rother)

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Roadshow on Funding possibilities in the field of digitalization and industrial technologies

04.03.2021 -

 Prof. Myra Spiliopoulou participates in the "Roadshow on Funding possibilities in the field of digitalization and industrial technologies (15 April 2021)" and reports on the Horizon 2020 Project UNITI under the title "UNITI - Medical research and Data Science jointly against tinnitus" (event in German)

URL: http://www.euhochschulnetz-sachsen-anhalt.de/eu_hsnetz/en/Events/Roadshow+on+Funding+possibilities+in+the+field+of+digitalization+and+industrial+technologies+%2815+April+2021%29.html

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Inspection of exam papers

Inspection of exam papers for Data Mining I / DM4BA and RecSys:Methods and applications

Thursday 22. March, 15:30 (update), R128

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Dates for oral exams (2nd try)

Dates for oral exams (2nd try):

Data Mining II, CRMRECSYS - January 29 and February 5, 2018

Please register at the Examinations Office

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Best Paper Award at ICBHI 2017

 

Best Paper Award (2. Position) at the Int. Conf. on Biomedical and Health Informatics (ICBHI 2017) for the Master DKE students Sourabh Dandage, Johannes Huber and Atin Janki: their paper

“Patient Empowerment through summarization of discussion threads on treatments in a patient self-help forum”

Authors: Sourabh Dandage, Johannes Huber, Atin Janki, Uli Niemann, Ruediger Pryss, Manfred Reichert, Steve Harrison, Markku Vessala, Winfried Schlee, Thomas Probst and Myra Spiliopoulou

is a followup of their teamproject on "How patients talk about their tinnitus". Link: here

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Last Modification: 16.06.2023 - Contact Person: