Course in Information Retrieval
|Lecturer||Jun.-Prof. Dr. Martin Potthast|
|Lab Advisors||Lukas Gienapp, Christopher Akiki|
|Workload||2 SWS Lecture, 1 SWS Lab|
|Lecture||Monday, 11:15 - 12:45, starting 12.04.2021, online|
|Lab||Tuesday, 9:15 - 10:45, starting 12.04.2021, online|
|Contact||Email, or via Discord server "irlecture"|
|Exam||Written exam, date to be announced.|
- Online sessions for the lab will take place every two weeks on Monday, 11:15 – starting 26/04/2021.
- Lectures are prerecorded. The videos can be accessed by following the lecturenotes below, or on the Webis youtube channel. [playlist]
- Online sessions will take place in the form of live Q&A sessions on BigBlueButton. These sessions are planned semi-regularly, each date will be announced on the course website.
- Lab material consists of biweekly programming exercises in the form of Jupyter notebooks.
- Examination will take place at the end of the semester as written online exam. Date is to be announced.
- Lecture website - materials and announcements will be uploaded on this website.
- Discord - there is a dedicated Discord server for this lecture to ask questions and engage in discussion. Check your mails for an access code. Please join the server and choose a Nickname such that we can identify you (at least surname).
- Email - important announcements will be sent out via mail.
- Information Retrieval » Introduction » Organization, Literature [video 1]
- Information Retrieval » Introduction » Retrieval Problems [video 2] [video 3] [video 4] [video 5] [video 6]
Information Retrieval »
Architecture of a Search Engine
- Natural Language Processing » Words » Text Preprocessing [video 15]
Natural Language Processing »
- Information Retrieval » Indexing » Indexing Basics [video 17]
Information Retrieval »
- Information Retrieval » Retrieval Models » Overview of Retrieval Models
- Information Retrieval » Retrieval Models » Empirical Models
The lab will be conducted as a series of exercises to give a hands-on experience for the concepts taught in the lecture. Each lecture block will be accompanied by a Jupyter notebook, which implements a component of a basic search engine.
Exercises will be published here every two weeks, with the solution following one week later. We will not collect & grade your exercise solutions, and participation in lab is not a prerequisite to the exam.
- 26/04/2021 - Session 01: Exercises 01 and 02
- 10/05/2021 - Session 02: Exercise 03
- 00 - Getting Started [download]
- 01 - Introduction to Python [view] [download]
- 02 - Introduction to Jupyter [view] [download]
- 03 - Text Analysis [view notebook] [download notebook] [download data] [view solution] [download solution]
- 04 - Indexing [view notebook] [download notebook] [download preprocess.py]