Course in Information Retrieval

General Information

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 TBA

Announcements

  • Lecture and Lab will take place online until further notice. throughout the semester.
  • Next Q&A session: Mon, 2020-06-08, 11:15 on BigBlueButton

Organization

  • 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 – when and in which form the Exam can take place is still to be determined. We will announce it here and via mail as soon as possible.
  • 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

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

  • 2020-04-07. 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

Lab Material

  • Literature
    • 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]
  • Data
    • Source corpus of ~380.000 arguments [link] (use "latest")
    • Training, evaluation and query data [link]
  • Example
    • Demo: [args.me]
    • 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.

Lab Report

A written report is expected at the end of the semester. Detailed information can be found below.

  • Language: English or German
  • Structure:
    1. Introduction
    2. Related Work
    3. Argument Retrieval Model(s) (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: TBA.
  • 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: TBA.