This web page gives information on the lecture 'Information Retrieval' which is held during the winter term 2020/2021 by Prof. Andreas Nürnberger.
The course will be 100% online via Zoom (lectures and exercises).
Students are requested to register to this course via LSF. The enrollment key to join Moodle will be emailed on the following dates:
1. 23rd Oct, 30th Oct
2. 6th Nov, 15th Nov
Information retrieval focuses on obtaining, extracting or mining information from a large collection of unstructured data, e.g. in form of text documents, images or videos. Information retrieval concepts are applied in web search engines, digital libraries and multimedia archives such as image and video databases. In this course the foundations of information retrieval will be introduced and illustrated on some specific application areas.
Master students, please note that this course is 5CP only!
The course provides an introduction to the principles, techniques, and applications of Machine Learning. Topics covered include among others (subject to change):
- value functions
- concept spaces and concept learning
- instance based learning
- decision trees
- neural networks
- Bayesian learning
- reinforcement learning
- association rule learning
- genetic algorithms
This course deals with selected topics and subdomains of the research
area "Data and Knowledge Engineering". With an emphasis on "Intelligent
Interactive Information Systems" students acquire insight in methods of
user behavior analysis and modeling, knowledge discovery and
visualization, data mining, adaptive retrieval systems etc. At the beginning of the course we will present topics but own ideas or suggestions are also welcome.
- Teacher: Johannes Schwerdt