Course in Information Retrieval

General Information

Lecturer Jun.-Prof. Dr. Martin Potthast
Lab Advisors Lukas Gienapp
Workload 2 SWS Lecture, 3 SWS Lab
Lecture Tuesdays, 13:15 - 14:45
Lab Tuesdays, 11:15 - 12:45
Contact Email, or via Discord server "irlecture"
Exam To be announced.


  • Final presentations have been scheduled - see Lab Sessions for more information.


  • Lectures are prerecorded. The videos can be accessed by following the lecturenotes below, or on the Webis youtube channel. [playlist]
  • Online sessions will additionally take place on BigBlueButton.
  • 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.


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

Lab Classes

  • 2020-10-27. Introduction [slides]
  • 2021-02-22. Final Presentations.
    Time Group
    12:00 Finn the Human
    12:30 Peter Pan
    13:00 Robin Hood
    13:30 The Bride
  • 2021-02-23. Final Presentations.
    Time Group
    10:30 Hua Mulan
    11:00 Mercutio
    11:30 He Man

Lab Material

  • Literature
    • Overview
      • Bondarenko et al. Overview of Touché 2020: Argument Retrieval. (CLEF 2020). [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 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 2
      • Schildwächter et al. Answering Comparative Questions: Better than Ten-Blue-Links? (CHIIR 2019). [link]
      • Panchenko et al. Categorizing Comparative Sentences. (ArgMining 2019). [link]
      • Chernodub et al. TARGER: Neural Argument Mining at Your Fingertips. (ACL 2019). [link]
  • Data
    • Data for is organized in a dedicated Git repository [link]
  • Example (Task 1)
    • Demo: []
    • Source: [Git]
    • Note that you do not need to implement a frontend in the lab. Your system only has to interact with Tira. Informations on Tira will be given in a dedicated lab session.
  • 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 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
  • Structure:
    1. Introduction
    2. Related Work
    3. Methodological Approach (i.e., a description of your contribution)
    4. Evaluation
    5. 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 28.02.2021
  • 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.