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:

  • to understand the progress of diseases and the long-term impact of interventions
  • to make recommenders adaptive to changing user interests and market conditions
  • to monitor opinions
  • to learn actively from the data, minimizing human effort.

Our methods are mostly in the field of stream mining. We develop stream mining methods, methods that exploit timestamped data, and dedicated stream algorithms for recommendation engines, opinion analysis, patient records and longitudinal epidemiological data.

Our research is reflected in our teaching programs. With KMD, students learn fundamentals of data mining and recommendation engines. They learn to design and apply mining and machine learning methods in realistic applications, and get involved in our research - in team projects and individual projects.

All our projects are listed here.


 

News

Scientific Team Projects Winter Term 21/22

19.10.2021 -

This semester, the KMD lab is offering topics for teamprojects.

Goal of the teamprojects is to enable students in solving complex real tasks in teamwork. In doing so, they use and occasionally extend methods they already learned in their studies thus far. They are exposed to the data science challenges of business understanding, of data preparation and of communicating the results to an application expert.

The application deadline is Oct. 28, 12:00.

More information and registration on Moodle/E-Learning: https://elearning.ovgu.de/course/view.php?id=11620

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Dates for LAST ATTEMPT exams in DM4BA, DM I, DM II, Recommenders, ITO, and WMS

28.09.2021 -

The dates for the LAST ATTEMPT exams in DM4BA, DM I, DM II, Recommenders, ITO, and WMS are:

January 31, 14:00 to 16:00    
January 31, 09:30 to 10:30
February 1, 13:00 to 15:00
   
NOTE: Last attempt exams are offered exclusively for degrees that prescribe a last attempt, and state that this attempt must be an oral exam.

The next slots for last attempt exams will be offered after the teaching period of winter term 2021/2022.
Important announcement regarding registration process:

In order to stay more compliant to the social distancing guidelines, the registration for the exam will be conducted slightly differently.

    Download, print, and fill out the examination registration form from the examination office. Fill all fields except the date and time.
    Submit the document to Mr. Knopke electronically. Deadline: January, 15.
    The next available time slot will be assigned to you, and Mr. Knopke forwards the updated form to the examination office. You will be informed about the date and time for your exam.

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Journal paper published at Special Issue "Analysis of FAIR Data from Medical Sensors" of the MDPI Journal "sensors" (IF 3.576)

06.08.2021 -

Journal publication in the ImmunLeanrning project: "Potential of Point-of-Care and At-Home Assessment of Immune Status via Rapid Cytokine Detection and Questionnaire-Based Anamnesis" by Noor Jamaludeen, Christian Beyer, Ulrike Billing, Katrin Vogel, Monika Brunner-Weinzierl and Myra Spiliopoulou


It is Noor Jamaludeen's first journal publication. Congratulations to all authors.

MORE:
Abstract: https://www.mdpi.com/1424-8220/21/15/4960
PDF Version: https://www.mdpi.com/1424-8220/21/15/4960/pdf
Special Issue: https://www.mdpi.com/journal/sensors/special_issues/FAIR_data

ImmunLearning: https://www.kmd.ovgu.de/Research/Medical+Mining/ImmunLearning.html

 

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Paper accepted in PLOS ONE

29.07.2021 -

Anne Rother's first-author paper, "Assessing the difficulty of annotating medical data in crowdworking with help of experiments", has been accepted in PLOS ONE. It is Anne's first scientific paper, which she wrote while still studying for her bachelor's degree. Congratulations on this great success!

Anne Rother, Uli Niemann, Tommy Hielscher, Henry Völzke, Till Ittermann, and Myra Spiliopoulou (2021). Assessing the difficulty of annotating medical data in crowdworking with help of experiments. PLOS ONE 16(7): e0254764. https://doi.org/10.1371/journal.pone.0254764

2021_Rother_PONE

 

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Paper accepted at IEEE DSAA 2021

26.07.2021 -

We are happy that Clara Puga's paper "Discovery of Patient Phenotypes through Multi-layer Network Analysis on the Example of Tinnitus", has been accepted at the IEEE International Conference on Data Science and Advanced Analytics 2021 (DSAA), which takes place in Porto, Portugal, 06-09 October. It is Clara's first scientific paper - Congratulations to her on this big achievement!

Clara Puga, Uli Niemann, Vishnu Unnikrishnan, Miro Schleicher, Winfried Schlee, and Myra Spiliopoulou: "Discovery of Patient Phenotypes through Multi-layer Network Analysis on the Example of Tinnitus"

2021_Puga_DSAA

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Uli Niemann defended his PhD thesis

17.06.2021 -

Uli Niemann successfully defended his Phd thesis titled „Intelligent Assistance for Expert-Driven Subpopulation Discovery in High-Dimensional Timestamped Medical Data“.

210617-phd-defense-uli

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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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Last Modification: 22.10.2021 - Contact Person:

Sie können eine Nachricht versenden an: Prof. Dr. Myra Spiliopoulou
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