DKE-Seminar and Project
Please register on the LSF but also on Moodle below!
On this page you can find information about the scientific seminar and project/practical course "Data and Knowledge Engineering", which takes place during the summer term 2021.
During the course this page will be updated continuously.
Content and Topics
This course deals with selected topics and subdomains of the research area "Data and Knowledge Engineering". Students acquire insight in methods of user behavior analysis and modeling, knowledge discovery and visualization, data mining, adaptive retrieval systems etc. Topics will be listed in the Moodle course!
At the beginning of the course we will present the suggested topics but own ideas or suggestions are also welcome. Topics may require knowledge about Machine Learning and/or Information Retrieval and many of them require knowledge about computer vision and deep learning. To choose a topic, it is important to have the required knowledge for it. Additionally, all topics involve a certain amount of programming. Therefore knowledge in a (relevant) programming language is necessary.
Please register yourself via LSF. Registrations will open until the 18th of April 2021. The seminar and project is limited to 10 participants. We apply the scheme: "First Come, First Serve" (FCFS). The topic distribution will be decided in the first dates of the course. I.e. if you have registered first and you are physically present at the first appointment, you can pick any of the presented topics. Anyone who is not present, will be skipped accordingly.
We will provide lecture slides, the choice of research topics during the course on Moodle: Link to the course
Dates and Rooms
Dates will be published on Moodle!
Further information to the course are found in the E-Learning Portal (Moodle) of the OVGU. Link to the course
If you have any questions about the course, please contact us via E-Mail:
- Afra'a Ahmad Alyosef
- Andreas Nürnberger
- Paper Template
- Presentation Template (Open Office)
- Online Sources
- Example of a very good paper
- Tips on Writing and Revising (by Katrin Krieger)