392101 Knowledge Representation (S) (SoSe 2026)
Contents, comment
-
The course covers foundational concepts and methods in Knowledge Representation and Reasoning (KR), addressing both theoretical foundations and practical applications. It focuses on symbolic and sub-symbolic approaches to representing, structuring, and reasoning over knowledge in intelligent systems.
Core topics include:
- First-Order Logic (FOL)
- Logic Programming and Automated Reasoning (Prolog programming, Rule-based reasoning)
- Structured Knowledge Representation (Frames, slots, and inheritance hierarchies)
- Semantic networks
- Knowledge graphs
- Resource Description Framework (RDF)
- Querying Knowledge Graphs (SPARQL, large-scale public knowledge graphs (e.g., Wikidata))
- Ontologies and Description Logics
The second part of the course focuses on Knowledge Graph Reasoning and Learning, including:
- Knowledge acquisition from structured and unstructured data
- Distributional semantics and word embeddings
- Knowledge graph embeddings
- Graph Neural Networks (GNNs) for knowledge representation
Advanced application topics include:
- Knowledge tracing
- Parametric knowledge in large language models
- Knowledge-graph-enhanced recommender systems
Requirements for participation, required level
-
Useful prior knowledge: Discrete Mathematics, Formal Logic, Introduction to Machine Learning
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period | |
|---|---|---|---|---|---|
| weekly | Di | 14-16 | X-E0-205 | 13.04.-24.07.2026 |
Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 39-Inf-WP-DS Data Science (Basis) Data Science (Basis) | Einführendes Seminar | Student information | |
| - | Graded examination | Student information | |
| 39-Inf-WP-DS-x Data Science (Focus) Data Science (Schwerpunkt) | Einführende Veranstaltung Seminar o. Vorlesung | Student information | |
| - | Graded examination | Student information | |
| 39-Inf-WP-KI Artificial Intelligence (Basis) Künstliche Intelligenz (Basis) | Einführendes Seminar | Student information | |
| - | Graded examination | Student information | |
| 39-Inf-WP-KI-x Artificial Intelligence (Focus) Künstliche Intelligenz (Schwerpunkt) | Einführende Veranstaltung Seminar o. Vorlesung | Student information | |
| - | Graded examination | Student information | |
| 39-M-Inf-AI-bas Basics of Artificial Intelligence Basics of Artificial Intelligence | Basics of Artificial Intelligence: Seminar | Student information | |
| - | Ungraded examination | Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
- Address:
- SS2026_392101@ekvv.uni-bielefeld.de
- This address can be used by teaching staff, their secretary's offices as well as the individuals in charge of course data maintenance to send emails to the course participants. IMPORTANT: All sent emails must be activated. Wait for the activation email and follow the instructions given there.
- If the reference number is used for several courses in the course of the semester, use the following alternative address to reach the participants of exactly this: VST_654011536@ekvv.uni-bielefeld.de
- Notes:
- Additional notes on the electronic mailing lists
- Last update basic details/teaching staff:
- Friday, December 12, 2025
- Last update times:
- Friday, February 6, 2026
- Last update rooms:
- Friday, February 6, 2026
- Type(s) / SWS (hours per week per semester)
- seminar (S) / 2
- Language
- This lecture is taught in english
- Department
- Faculty of Technology
- Questions or corrections?
- Questions or correction requests for this course?
- Planning support
- Clashing dates for this course
- Links to this course
- If you want to set links to this course page, please use one of the following links. Do not use the link shown in your browser!
- The following link includes the course ID and is always unique:
- https://ekvv.uni-bielefeld.de/kvv_publ/publ/vd?id=654011536
- Send page to mobile
-
Click to open QR code
Scan QR code:
- ID
- 654011536