Course Registration

Time:
until 20.10.2009

Place:
wherever you are (email!)

Additional information:

There are still free places in this course!

You have to registrate first to become a member of it. For course registration please send a mail with your name and your matriculation number to 'dirk@isg.cs.uni-magdeburg.de', with the subject 'VA VDM'. You'll get an email to confirm your membership immediately.
Hint: This course is for bachelor and diploma (unfortunately not for master) students.


Visual Analytics and Visual Data Mining
High-dimensional datasets with a huge number of datavalues are often generated during common working processes in business and science. The goal of Visual Analytics & Visual Data Mining is to handle these datasets with the aid of the human cognition.

Here, the term ''handle'' means to identify major patterns and
textures to be able to describe the relationships between the dimensions itself, like correlations, clusters or bifurcations. To do that, the first step is to generate significant (and often ranked) visualizations from the dataset (VDM). The second step is to integrate these visualizations (and the visualization-process) in an interactive system (VA), with that a human is able to interpret the dataset completely.

To sum up, the questions that should be answered are:
- Which approaches of visualization are appropriate?
- How does an interactive system should looks like ?

Topics will be assigned at the first meeting.


Lecturer:
Dirk J. Lehmann, Steffen Oeltze, Prof. Bernhard Preim, Prof. Holger Theisel
Dates:
tba
Classification:
WPF CV;i ab 8
WPF CV;B ab 5 (ECTS-Credits: 3)
WPF CSE;B ab 5 (ECTS-Credits: 3)
WPF IF;i ab 8
WPF IF;B ab 5 (ECTS-Credits: 3)
WPF INGIF;i ab 8
WPF WIF;i ab 8
WPF WIF;B ab 5 (ECTS-Credits: 3)
Requirements:
basic knowledge in visualization, linear algebra, image processing and theory of cognition
Certificate/Schein:
- compulsory attendance
- 30 min. presentation + 15 min. discussion
- exposition (at least 3 pages, at most 5 pages)
Additional Information:
> Lecture website <
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