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This entry is from Winter semester 2016/17 and might be obsolete. You can find a current equivalent here.

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): Oral or written examination
Examination type: Successful completion of at least 50 percent of the points from the weekly exercises as well as at least 2 presentations of the tasks.
Language,
Grading		 German,
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

Students should

  • Gain knowledge of the most important models for information retrieval,
  • get an overview of the architecture of IR systems,
  • Know indexing techniques,
  • Understand optimization of queries in IR,
  • acquire knowledge in applications of IR in the field of web and multimedia,
  • practice scientific working methods (recognizing, formulating, solving problems, training the ability of abstraction),
  • practice oral communication skills in the exercises by practicing free speech in front of an audience and in discussion.

Prerequisites

Translation is missing. Here is the German original:

Keine. Empfohlen werden die Kompetenzen, die in dem Modul Algorithmen und Datenstrukturen vermittelt werden


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
  • B.Sc. Business Informatics
  • M.Sc. Data Science
  • M.Sc. Computer Science
  • M.Sc. Mathematics
  • M.Sc. Business Informatics
  • 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 2016/17. 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.