I'm working on two Information Retrieval courses at the Vienna University of Technology (TU Wien), mainly focusing on the master-level Advanced Information Retrieval course. I try to create engaging, fun, and invormative lectures and exercises.
- The Introduction to Information Retrieval course focuses on IR basics and engineering skills of the students.
- The Advanced Information Retrieval course focuses on machine learning & neural IR techniques and tries to follow the state-of-the-art in IR research.
Please feel free to open up an issue or a pull request if you want to add something, find a mistake, or think something should be explained better!
Information Retrieval is the science behind search technology. Certainly, the most visible instances are the large Web Search engines, the likes of Google and Bing, but information retrieval appears everywhere we have to deal with unstructured data (e.g. free text).
A paradigm shift. Taking off in 2019 the Information Retrieval research field began an enormous paradigm shift towards utilizing BERT-based language models in various forms to great effect with huge leaps in quality improvements for search results using large-scale training data. This course aims to showcase a slice of these advances in state-of-the-art IR research towards the next generation of search engines.
The AIR'21 syllabus overview
In the following we provide links to recordings, slides, and closed captions for our lectures. (Continuously adding more throughout the semester March-June 2021)
| Topic | Description | Recordings | Slides | Closed Captions |
|---|---|---|---|---|
| 0: Introduction | Infos on requirements, topics, organization | YouTube | GitHub | |
| 1: Crash Course IR Fundamentals | We explore two fundamental building blocks of IR: indexing and ranked retrieval | YouTube | GitHub | |
| 2: Crash Course IR Evaluation | We explore how we evaluate ranked retrieval results and common IR metrics (MRR, MAP, NDCG) | YouTube | GitHub |