The course presents an introduction to the field of information retrieval and discusses automated techniques to effectively handle and manage unstructured and semi-structured information. This includes methods and principles that are at the heart of various systems for information access, such as Web or enterprise search engines, categorization and recommended systems, as well as information extraction and knowledge management tools.
The plan for exercise classes: there will be 3 or 4 small programming projects which one of them is optional and the rest are mandatory. In other words, in order to pass the course you need to hand in all, except one, of the projects. It's up to you to choose which project to skip. Projects will be done by groups of 3 or 4 students. Please form (or join) a group as soon as possible and let the TAs know. The projects results and artifacts will be discussed face to face in exercise classes. Moreover, some of the exercise sessions are reserved for giving tutorials on the subjects that are not fully covered in lectures (mainly, the necessary mathematical basics). The exact schedule for these tutorials will be announced in advance.
Course Materials
See here
Lecturer
Prof. Thomas Hofmann
TAs
Anja Grünheid
Simon Lösing
Language
English
Syllabus
- Introduction
- Vocabulary and Dictionaries
- Boolean Retrieval Model
- Index Construction and Compression
- Vector Space Model
- IR Evaluation
- Relevance Feedback and Query Expansion
- Text Categorization
- Document Clustering
- Web Search
- Link Analysis
Schedule
- Lecture: Wed 09:00 - 11:00 ML F 34
- Exercise: Wed 11:00 - 12:00 ML F 34
Literature
C. Manning, P. Raghavan, H. Schütze: Introduction to Information Retrieval, 2008, Cambridge University Press. Online version available here.
