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CS 529 — Algorithmic Network Analysis
(dt. Algorithmische Netzwerkanalyse)

Level, degree of commitment Specialization module, compulsory elective module
Forms of teaching and learning,
workload		 Lecture (3 SWS), recitation class (1 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. Computer Science.
Duration,
frequency		 One semester,
irregular
Person in charge of the module's outline Prof. Dr. Christian Komusiewicz

Contents

  • Applications of network models such as social networks, biological interaction networks.
  • Algorithms and complexity considerations for computational problems in network analysis, such as computing measures of centrality, clustering networks, querying networks, enumerating subnetworks
  • Random models for complex networks
  • Advanced network models: temporal graphs, multilayer networks

Qualification Goals

Students can model various issues using networks and formulate various analysis tasks as concrete computational problems. For these computational problems, they can select or design efficient algorithms or show that such algorithms do not exist according to current thinking.


Prerequisites

The following module is required: Algorithms and Data Structures. In addition, successful participation in the module „Effiziente Algorithmen“ (Efficient Algorithms) is recommended.


Applicability

Module imported from M.Sc. Computer 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

When studying M.Sc. Data Science, this module can be attended in the study area Free Compulsory Elective Modules.

The module is assigned to Computer Science. Further information on eligibility can be found in the description of the study area.


Recommended Reading

  • Borgatti, Everett, Johnson: Analyzing social networks. SAGE, 2018.
  • Brandes, Erlebach (eds.): Network analysis: Methodological foundations. Lecture Notes in Computer Science, volume 3418, Springer 2005.



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2023/24. 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:

  • Winter 2016/17 (no corresponding element)
  • Summer 2018 (no corresponding element)
  • Winter 2018/19 (no corresponding element)
  • Winter 2019/20 (no corresponding element)
  • Winter 2020/21 (no corresponding element)
  • Summer 2021 (no corresponding element)
  • Winter 2021/22 (no corresponding element)
  • Winter 2022/23 (no corresponding element)
  • Winter 2023/24

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.