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CS 572 — Information Retrieval
(dt. Information Retrieval)

Level, degree of commitment Specialization module, compulsory elective module
Forms of teaching and learning,
workload		 Lecture (2 SWS), recitation class (2 SWS),
180 hours (60 h attendance, 120 h private study)
Credit points,
formal requirements		 6 CP
Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises as well as at least 2 presentations of the tasks.
Examination type: Oral examination (individual examination) or written examination
Language,
Grading		 English,
The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Data Science.
Duration,
frequency		 One semester,
Zweijährlich im Sommersemester
Person in charge of the module's outline Prof. Dr. Bernhard Seeger

Contents

  • Quality criteria for information retrieval
  • Models for Information Retrieval
  • Architecture of Information Retrieval Systems
  • Index Methods and Index Structure
  • query extension
  • IR and Web
  • multimedia retrieval

Qualification Goals

Translation is missing, sorry. German original:

Die Studierenden

  • können die wichtigsten Modelle für das Information Retrieval beschreiben,
  • können die Architektur von IR Systemen erläutern,
  • können Indexierungstechniken benennen,
  • können die Optimierung von Anfragen in IR beschreiben,
  • können IR im Bereich Web und Multimedia anwenden,
  • können wissenschaftliche Arbeitsweisen (Erkennen, Formulieren, Lösen von Problemen, Schulung des Abstraktionsvermögens) anwenden,
  • sind in der Lage, über wissenschaftliche Inhalte frei zu sprechen, sowohl vor einem Publikum als auch in einer Diskussion.

Prerequisites

None. The competences taught in the following modules are recommended: either Algorithms and Data Structures or Practical Informatics II: Data Structures and Algorithms for Pre-Service-Teachers.


Applicability

Module imported from M.Sc. Data Science.

It can be attended at FB12 in study program(s)

  • B.Sc. Data Science
  • B.Sc. Computer Science
  • M.Sc. Data Science
  • M.Sc. Computer Science
  • M.Sc. Mathematics
  • M.Sc. Business Informatics
  • M.Sc. Business Mathematics
  • LAaG Computer Science

When studying LAaG Computer Science, this module can be attended in the study area Specialization Modules.


Recommended Reading

  • Manning, Raghavan, Schütze: Introduction to Information Retrieval, Cambridge University Press
  • Baeza-Yates, Ribeiro-Neto: Modern Information Retrieval, Addison Wesley
  • Ferber: Information Retrieval-Suchmodelle und Data-Mining-Verfahren für Textsammlungen und das Web, dpunkt Verlag
  • Henrich: Information Retrieval - Grundlagen, Modelle und Anwendungen



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2025/26. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.