Information Retrieval
Basic information
Lecturer: Prof. Dr. Goran Glavaš
Teaching Assistants: Benedikt Ebing, Fabian David Schmidt
Lectures: Tuesday, 10-12 in Übungsraum II
Exercises: in two groups (i) Wednesday 10-12 SE I and (ii) Thursday 10-12 SE II
Kickoff: 25.4.2023
Intended audience: The course is recommended for master students of all CS-oriented programs (Master Informatik, Master eXtended AI, Master Business Informatics). Prior knowledge of core NLP and machine learning concepts is desirable, albeit not mandatory.
Registration
It is not necessary to register for the lecture or exercises.
In order to get access to teaching materials and current announcements you need to register for WueCampus course
To participate in the exam you must register for the exam via WueStudy.
All further information on this can be found in our WueCampus course
Learning outcomes
Students will acquire knowledge of fundamental techniques of Information Retrieval, including traditional and neural/semantic retrieval models, how to evaluate IR systems, and how to exploit the linked nature of the web for web search.
Schedule (tentative)
25.4. L1: Intro to IR; Course organization
2.5. L2: Boolean Retrieval
9.5. L3: Tolerant Retrieval
16.5. L4: Vector Space Model
23.5. L5: Probabilistic IR
30.5. L6: Language Modeling Retrieval
6.6. L7: Query Expansion & Relevance Feedback
13.6. L8: Latent/Semantic Retrieval
20.6. L9: Clustering, Classification, and Learning to Rank
27.6. L10: Neural Retrieval, Preranking-Reranking
4.7. L11: Evaluation
11.7. L12: Web Search
18.7. Project presentations* (smaller-scale projects for exam grade bonus)
