Course in Advanced Information Retrieval
General Information
Lecturer | Jun.-Prof. Dr. Martin Potthast |
Lab Advisors | Theresa Elstner |
Workload | 2 SWS Lecture, 3 SWS Lab |
Lecture | Tuesdays, 11:15 - 12:45 - |
Lab | Tuesdays, 13:15 - 14:45 - |
Contact | Email, or via Discord server "irlecture" |
Exam | To be announced. |
Announcements
- Final Presentations on February, 1st 2022 9:00 - 11:00 h.
- Changed required template format for final report: [Latex Template]
Organization
- Some Lectures are additionally available as videos. The videos can be accessed by following the lecturenotes below, or on the Webis youtube channel. [playlist]
- Lab participation is a prerequisite to complete the module.
- Communication
- 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.
Lecturenotes
- Information Retrieval » Introduction » Organization, Literature [video 1]
- Information Retrieval » Introduction » Retrieval Problems [video 2] [video 3] [video 4] [video 5] [video 6]
-
Information Retrieval »
Introduction »
Architecture of a Search Engine
[video 7]
[video 8]
[video 9]
[video 10]
[video 11]
[video 12]
[video 13]
[video 14]
- Information Retrieval » Indexing » Indexing Basics [video 15]
- Natural Language Processing » Words » Text Preprocessing [video 16]
- Natural Language Processing » Words » Morphological Analysis [video 17]
-
Information Retrieval »
Indexing »
Inverted Index
[video 18]
[video 19]
[video 20]
[video 21]
- Information Retrieval » Evaluation » Laboratory Experiments [video 30]
- Information Retrieval » Evaluation » Effectiveness Measures [video 31] [video 32] [video 33]
-
Information Retrieval »
Evaluation »
Training and Testing
[video 34]
- Information Retrieval » IR Applications » Argument Search [video 35] [video 36] [video 37] [video 38] [video 39]
- Information Retrieval » Retrieval Models » Overview of Retrieval Models [video 22]
- Information Retrieval » Retrieval Models » Empirical Models [video 23]
- Machine Learning » Statistical Learning » Probability Basics [video 24] [video 25]
- Machine Learning » Statistical Learning » Bayes Classification [video 26]
- Information Retrieval » Retrieval Models » Probabilistic Models [video 27] [video 28]
-
Information Retrieval »
Retrieval Models »
Generative Models
[video 29]
Lab Project
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.
Lab Lecturenotes
- Lecturenotes Generic » Scientific Toolbox » Literature Research [video 1]
- Lecturenotes Generic » Scientific Toolbox » Oral Presentations [video 2]
- Lecturenotes Generic » Scientific Toolbox » Scientific Writing [video 3]
Lab Classes
- 2021-10-27. Introduction [slides]
- 2022-01-25. Final Presentations
Time Group 11:00 Korg 11:30 Pearl 12:00 Goldar 12:30 Boromir - 2022-02-01. Final Presentations
Time Group 09:00 Hit-Girl 09:30 Porthos 10:00 Jester 10:30 Aramis
Lab Material
- Literature
- Overview
- Bondarenko et al. Overview of Touché 2021: Argument Retrieval. (CLEF 2021). [link]
- Task 1
- 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]
- Task 3
- Kiesel et al. Image Retrieval for Arguments Using Stance-Aware Query Expansion. (ArgMining 2021). [link]
- Dimitrov et al. SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images. (SemEval 2021). [link]
- Yanai Image collector III: a web image-gathering system with bag-of-keypoints. (WWW 2007). [link]
- Data
- Data is organized in a dedicated Git repository [link]
- Example (Argument Search)
- TIRA
- Check your groups Discord channel for credentials!
- Quickstart Guide [quickstart]
- Video Tutorial [video]
- Tutorial Code [git]
Lab Report
A written report is expected at the end of the semester. Note that grades will be based on the lab report and on the final presentation. Detailed information on what is expected of the report and the talk can be found below.
- Language: English or German
- Structure:
- Introduction
- Related Work
- Methodological Approach (i.e., a description of your contribution)
- Evaluation
- Discussion and Conclusion
- Style: please use the following template for your report [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 28.02.2022
- 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.