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 06.04.2020, HS 19|
|Lab||Tuesday, 9:15 - 10:45, starting 07.04.2020, HS 19|
|Contact||Email, or via Discord server "irlecture"|
|Exam||This semester, the grade will be based on the lab project only. No written exam!|
- Lecture and Lab will take place online
until further notice.
- Next Q&A session: Mon, 2020-06-15, 11:15 on BigBlueButton
- 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 weekly Q&A sessions on BigBlueButton. Since these sessions can alternate between Mondays and Tuesdays, each date will be announced on the course website.
- Lab participation is a prerequisite to complete the module. Check out the introduction video on lab organization below.
- Exam This semester, the grade will be based on the lab project only. No written exam!
- Lecture website - materials and announcements will be uploaded on this website.
- Discord - there is a dedicated Discord server for this lecture. Check your mails for an access code. There are different channels for questions regarding lecture and lab, group finding, and each lab group will get a dedicated channel for internal communication. 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
- Information Retrieval » Indexing » Indexing Basics [video 15]
Information Retrieval »
- Natural Language Processing » Words » Text Preprocessing [video 20]
Natural Language Processing »
- Information Retrieval » Evaluation » Laboratory Experiments [video 22]
Information Retrieval »
- Information Retrieval » IR Applications » Argument Search [video 26] [video 27] [video 28] [video 29] [video 30]
The lab consists of building and evaluating an information system for a specific domain. This entails related work search, data cleansing, indexing, selection and implementation of suitable retrieval models, evaluation of search quality, and the submission of a written report and well-documented source code.
- Lecturenotes Generic » Scientific Toolbox » Literature Research [video 1]
- Lecturenotes Generic » Scientific Toolbox » Oral Presentations [video 2]
- Lecturenotes Generic » Scientific Toolbox » Scientific Writing [video 3]
- Information Retrieval » Practical Sessions » Introduction to Tira.io [video 4] [material]
- 2020-04-07. Introduction. [shared task] (you do not need to register) [slides] [video]
- 2020-05-11. Virtual Group Meetings
- 2020-05-12. Virtual Group Meetings
- 2020-05-18. Virtual Group Meetings
- 2020-05-19. Virtual Group Meetings
- 2020-06-02. Virtual Group Meetings
- 2020-06-08. Virtual Group Meetings
- 2020-06-09. Virtual Group Meetings
- 2020-06-29. Virtual Group Meetings
- 2020-07-05. Virtual Group Meetings
- Mon. 2020-09-14. Project Presentations.
Time Group 10:00 Mazarin 10:30 Portales 11:00 Marsac 13:00 Peyrer 13:30 Artagnan
- Tue. 2020-09-15. Project Presentations.
Time Group 10:30 Vestric 11:00 Colbert
- Wachsmuth et al. Building an Argument Search Engine for the Web (ArgMining 2017). [link]
- Ajjour et al. Data Acquisition for Argument Search: The args.me corpus. (KI 2019). [link]
- Potthast et al. Argument Search: Assessing Argument Relevance. (SIGIR 2019). [link]
- Wachsmuth et al. Computational Argumentation Quality Assessment in Natural Language. (EACL 2017). [link]
- Bondarenko et al. Touché: First Shared Task on Argument Retrieval. (ECIR 2020). [link]
A written report is expected at the end of the semester. Note that since we are not able to conduct a written exam this semester, grades will be based only the lab report. Detailed information on whats expected of the report can be found below.
- Language: English or German
- Related Work
- Argument Retrieval Model(s) (i.e., a description of your contribution)
- Discussion and Conclusion
- Style: please use Springer LNCS as template for your report [Overleaf Template] [Word Template] [Latex Template]
- Length: minimum 10 pages.
- Supplementary Material:
- your source code in a git repository with full commit history
- a working deployment of your system on the Tira platform
- Due Date: reports have to be turned in on 31.08.2020
- Talk: in addition to the report, we will have short (~20min + questions) talks with each group at the end of the semester. Each person of the group should have their fair share of talking and the talk should cover all important aspects of your approach.