KMD Events

Klausureinsicht Informationstechnologie in Organisationen

02.05.2017 -

Klausureinsicht Informationstechnologie in Organisationen

am Donnerstag, den 18.5.2017 von 14:00-14:45 in R310.

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Topics for the Summer Term 2017

Under the following links, students will find the project and seminar topics for the summer term 17:

Myra's Topics

Pawel's Topics

Tommy's Topics

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Data Mining Exam Review

27.02.2017 -

The review of the Data Mining exam (WS16/17) will take place on

March 15th, 15:00 - 16:00 in room G29-135.

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Tutorial @ PAKDD 2013

14.12.2016 -

Myra Spiliopoulou and Georg Krempl will present a Tutorial on Mining Multiple Threads of streaming Data at PAKDD 2013, April 14-17, Gold Coast, Australia.

Stream mining is a mature area of research. However, several applications that require adaptive learning from evolving data do not seem to fit to the conventional stream mining paradigm. For example, a bank grants loans to customers and uses their data for model learning; the label (loan-payed-back YES or NO) arrives some years later, though, during which years the market may have changed drastically. Is this a stream mining problem? How many streams are there? We can distinguish between the stream of customers and the stream of their labels, which arrive with a time lag of years.

As another example, a hospital monitors patients with chronical diseases that come (ir)regularly to the hospital and undergo different tests; the streams of medical recordings and of signals (EEG, fMRI) can be used for learning. The hospital wants to learn a model on how the patients' health evolves in response to the disease and to medications. This problem seems completely different from the previous one, albeit streams of data are there in both cases.

In this tutorial, Myra Spiliopoulou and Georg Krempl bring together research advances on model learning and adaption for dynamic applications that collect and analyze different sources of dynamic data. In the introductory part of the tutorial, they present the classic stream mining paradigm and summarize the challenges being investigated in the state-of-the-art research.

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Lecture slides are going offline

14.12.2016 -

Beginning with the 20th of December, lecture slides will be no longer available through our website.

Exception: ITO lecture slides will go offline on the 16th of December (early morning).

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