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Instructors: Prof. Dr. Ricardo Usbeck
Event type:
Introductory seminar
Displayed in timetable as:
PS Semantics
Hours per week:
2
Credits:
3,0
Language of instruction:
German
Min. | Max. participants:
- | 20
Registration group: Anmeldegruppe Proseminare
Comments/contents:
Semantics is the basis for machines to understand us and our texts. Knowledge graphs are the best-known data model for representing semantics. Today, they are often the basis of data engineering in the field of artificial intelligence. In order to use knowledge graphs, one needs a variety of technologies, including knowledge about the creation, validation, and use of knowledge graphs using and in the natural language processing environment.
After a general introduction to the technology, students will delve into a selected topic and develop a short talk and blog post with a poster on that topic.
The list of topics and related literature will be developed in the plenary in the first seminar, see also Moodle. For this purpose, we will develop a focus topic, e.g. fake news detection.
You are welcome to present your own knowledge graph-based NLP application around the focus topic.
Learning objectives:
Students will be able to identify, evaluate and, if necessary, use current knowledge graphs and their areas of application. Students will have key skills in the area of independent research, structuring, presenting (blog, poster, lecture) and moderating a discussion following the lecture.
Didactic concept:
Please find all further information in ?https://lernen.min.uni-hamburg.de/course/view.php?id=2132
Additional examination information:
Course Credits: Submission of written assignments (blog, poster, slides) by the end of the lecture period on January 29, 2022.
Examination Credits: The blog, poster, presentation and slides for the presentation will be evaluated according to a previously accessible evaluation form (see moodle).
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