Module Handbook

  • Dynamischer Default-Fachbereich geändert auf INF

Module INF-71-58-M-5

Collaborative Intelligence (M, 4.0 LP)

Module Identification

Module Number Module Name CP (Effort)
INF-71-58-M-5 Collaborative Intelligence 4.0 CP (120 h)

Basedata

CP, Effort 4.0 CP = 120 h
Position of the semester 1 Sem. in SuSe
Level [5] Master (Entry Level)
Language [EN] English
Module Manager
Lecturers
Area of study [INF-KI] Intelligent Systems
Reference course of study [INF-88.79-SG] M.Sc. Computer Science
Livecycle-State [NORM] Active

Courses

Type/SWS Course Number Title Choice in
Module-Part
Presence-Time /
Self-Study
SL SL is
required for exa.
PL CP Sem.
2V+1U INF-71-58-K-5
Collaborative Intelligence
P 42 h 78 h
U-Schein
ja PL1 4.0 SuSe
  • About [INF-71-58-K-5]: Title: "Collaborative Intelligence"; Presence-Time: 42 h; Self-Study: 78 h
  • About [INF-71-58-K-5]: The study achievement "[U-Schein] proof of successful participation in the exercise classes (ungraded)" must be obtained.
    • It is a prerequisite for the examination for PL1.

Examination achievement PL1

  • Form of examination: written exam (Klausur) (60-90 Min.)
  • Examination Frequency: each semester
  • Examination number: 67158 ("Collaborative Intelligence")

Evaluation of grades

The grade of the module examination is also the module grade.


Contents

  • Methods for supporting personal knowledge work
  • Organizational Memories
  • Modeling of attention and activity context
  • Basics of Information Retrieval
  • Searching in location-, task-, and interest-based contexts
  • Agile knowledge-workflows and emergent systems
  • Enterprise platforms and social networks
  • Factors of success and evaluation methods

Competencies / intended learning achievements

By successfully completing the module, students will be able to
  • describe and apply basic techniques of information retrieval and web mining,
  • evaluate multimodal forms of interaction with information (e.g. information provision, context modelling, user observation) and apply them to practical problems
  • compare relevant concepts and procedures for information sharing in socio-technical, collaborative environments and develop solutions for practical problems,
  • explain the choice of appropriate methods and technologies to support knowledge-intensive activities,
  • analyze the advantages and disadvantages of using Collaborative Intelligence in the application context
  • validate the strengths and weaknesses of semantic technologies depending on the application context and assess their potential in the business context

Literature

  • Semantische Technologien: Grundlagen – Konzepte – Anwendungen, Andreas Dengel (Ed), Spektrum Akademischer Verlag, 2012
  • Introduction to Information Retrieval, Christopher D. Manning et al, Cambridge University Press., 2008
  • Foundations of Semantic Web Technologies, P Hitzler, M Krotzsch, S Rudolph. Chapman and Hall/CRC, 2010
  • Artificial Intelligence: A Modern Approach, Stuart Jonathan Russell, Peter Norvig. Prentice Hall, 2010

Requirements for attendance of the module (informal)

None

Requirements for attendance of the module (formal)

None

References to Module / Module Number [INF-71-58-M-5]

Course of Study Section Choice/Obligation
[INF-88.79-SG] M.Sc. Computer Science [Specialisation] Specialization 1 [WP] Compulsory Elective
Module-Pool Name
[INF-KI_Ba_V-MPOOL-4] Specialization Bachelor TA Intelligent Systems
[INF-SIAK-DT-AI-MPOOL-6] SIAK Certificate "Digital Transformation" - Modules INF "Artificial Intelligence"
[MV-MBINFO-MPOOL-6] Wahlpflichtmodule Maschinenbau mit angewandter Informatik