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| It takes place every Tuesday from 14:'''05''' - 15:'''50''' h in the seminar room [[https://mm.informatik.uni-freiburg.de/room/101-1-9|101-1-9/13]] and on Zoom ([[https://uni-freiburg.zoom.us/|meeting link]], meeting ID: <TODO>, passcode: IRWS23/24). The first lecture is on Tuesday 17.10.2023 and the last lecture is on Tuesday 06.02.2024. There will be no lectures on the Tuesdays 26.12.2023 and 02.01.2024 (Christmas break). | It takes place every Tuesday from 14:'''05''' - 15:'''55''' h in the seminar room [[https://mm.informatik.uni-freiburg.de/room/101-1-9|101-1-9/13]] and on Zoom ([[https://uni-freiburg.zoom.us/j/66883835704?pwd=eDNSNWdML3BvREhUTE03V3d5VS9BUT09|meeting link]], meeting ID: 668 8383 5704, passcode: IRWS23/24). The first lecture is on Tuesday 17.10.2023 and the last lecture is on Tuesday 06.02.2024. There will be no lectures on the Tuesdays 26.12.2023 and 02.01.2024 (Christmas break) and on two additional Tuesdays not determined yet. In total there will be 13 lectures. |
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| * The [[https://daphne.informatik.uni-freiburg.de/forum/|forum]] for announcements and questions. | * The [[https://daphne.informatik.uni-freiburg.de/forum/viewforum.php?f=1281|forum]] for announcements and questions. |
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| * Our [[https://daphne.informatik.uni-freiburg.de/CodingStandards/svn|CodingStandards]] for Python 3. * Information about Subversion (SVN) can be found [[SVN|here (in German)]] and [[SVNEnglish|here (in English)]]; about some editors (including Vim) [[Editoren|here (in German)]]; and about the installation of gtest (for C++ only) [[Manuals/Gtest|here (in English)]]. |
* Information about Subversion (SVN) can be found [[SVN|here (in German)]] and [[SVNEnglish|here (in English)]]; about some editors (including Vim) [[Editoren|here (in German)]]. |
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| * Here you can download our [[InformationRetrievalWS2324/LinuxImage|Linux Image]] (for Virtualbox or VMWare). | * [[InformationRetrievalWS2324/PythonEnv|Here]] you find a list of the Python packages you should have installed in your environment. Alternatively you can download and use our [[InformationRetrievalWS2324/LinuxImage|Linux Image]] (for Virtualbox or VMWare) which already contains all packages. |
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| * [[https://youtu.be/96r3iqJhx8Y|Here]] you can find a link to a video tutorial about how to work on the exercise sheets with our course system Daphne and SVN. | |
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* Lecture 1, Tuesday, October 17, 2023 (Introduction, Inverted Index, Zipf's Law): <<BR>>[[https://youtu.be/iSmGBkSkMvg|Video recording]] ([[https://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS2324/lecture-01.mp4|MP4 Download]]), [[https://daphne.informatik.uni-freiburg.de/ws2324/InformationRetrieval/svn/public/slides/lecture-01.pdf|Slides]], [[https://daphne.informatik.uni-freiburg.de/ws2324/InformationRetrieval/svn/public/exercises/sheet-01.pdf|Exercise Sheet 1]], [[https://daphne.informatik.uni-freiburg.de/ws2324/InformationRetrieval/svn/public/code/lecture-01/|Code from the lecture]], [[https://daphne.informatik.uni-freiburg.de/ws2324/InformationRetrieval/svn/public/templates/sheet-01/|Code template for ES1]], [[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS2324/datasets/movies.tsv|Dataset for ES1]] (115,454 movies with title + description + 3 columns with scores that you can ignore for this sheet). Note: If the dataset download does not start automatically when clicking the link, copy the link address and paste it in a new tab or download it using the wget command. |
Welcome to the Wiki of the course "Information Retrieval" in the winter semester 2023/2024
The course is given by Prof. Dr. Hannah Bast and assisted by Sebastian Walter. It takes place every Tuesday from 14:05 - 15:55 h in the seminar room 101-1-9/13 and on Zoom (meeting link, meeting ID: 668 8383 5704, passcode: IRWS23/24). The first lecture is on Tuesday 17.10.2023 and the last lecture is on Tuesday 06.02.2024. There will be no lectures on the Tuesdays 26.12.2023 and 02.01.2024 (Christmas break) and on two additional Tuesdays not determined yet. In total there will be 13 lectures.
The tutors for this course are Daniel Bindemann, Patrick Brosi, Johannes Kalmbach, Natalie Prange and Robin Textor-Falconi. The administrator of the supporting systems (Daphne, SVN, Forum, Jenkins) is Axel Lehmann.
Important Links
Our course management system Daphne (login with your RZ user name and password).
The forum for announcements and questions.
The manual for how to ask questions on the forum.
Our rules for the exercise sheets. Please read them carefully, completely and before you start working on the exercises. They are valid for all exercise sheets of this course.
Information about Subversion (SVN) can be found here (in German) and here (in English); about some editors (including Vim) here (in German).
The courses from previous semesters: Information Retrieval WS 22/23, Information Retrieval WS 21/22, Information Retrieval WS 19/20, Information Retrieval WS 18/19, Information Retrieval WS 17/18, Information Retrieval WS 16/17, Information Retrieval WS 15/16, Information Retrieval WS 13/14, Information Retrieval WS 12/13.
The exams from previous semesters: WS 22/23, WS 21/22, WS 19/20, WS 18/19, WS 17/18, WS 16/17, WS 15/16, WS 13/14, WS 12/13.
Here you find a list of the Python packages you should have installed in your environment. Alternatively you can download and use our Linux Image (for Virtualbox or VMWare) which already contains all packages.
An overview over basic tensor usage within PyTorch can be found here. If you are already familiar with NumPy you can find information about how NumPy operations translate to PyTorch operations here.
Here you can find a link to a video tutorial about how to work on the exercise sheets with our course system Daphne and SVN.
Lecture Slides, Video Recordings, Exercise Sheets, and Code
For visitors from outside the University of Freiburg: You can freely access all the course materials below, except the solutions, by replacing /svn/ by /svn-public/ in the URL.
Lecture 1, Tuesday, October 17, 2023 (Introduction, Inverted Index, Zipf's Law):
Video recording (MP4 Download), Slides, Exercise Sheet 1, Code from the lecture, Code template for ES1, Dataset for ES1 (115,454 movies with title + description + 3 columns with scores that you can ignore for this sheet). Note: If the dataset download does not start automatically when clicking the link, copy the link address and paste it in a new tab or download it using the wget command.