Module Handbook

  • Dynamischer Default-Fachbereich geändert auf INF

Course INF-71-63-K-6

Social Web Mining (2V+1U, 4.0 LP)

Course Type

SWS Type Course Form CP (Effort) Presence-Time / Self-Study
- K Lecture with exercise classes (V/U) 4.0 CP 78 h
2 V Lecture 28 h
1 U Exercise class (in small groups) 14 h
(2V+1U) 4.0 CP 42 h 78 h

Basedata

SWS 2V+1U
CP, Effort 4.0 CP = 120 h
Position of the semester 1 Sem. in SuSe
Level [6] Master (General)
Language [EN] English
Lecturers
Area of study [INF-KI] Intelligent Systems
Livecycle-State [NORM] Active

Possible Study achievement

  • Verification of study performance: proof of successful participation in the exercise classes (ungraded)
  • Details of the examination (type, duration, criteria) will be announced at the beginning of the course.

Contents

  • RESTful APIs
  • RSS and Atom Syndication
  • Web Crawling and Web Scraping
  • Data Mining
  • Text Mining
  • Network Mining

Literature

  • Russell, Matthew A. Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More. " O'Reilly Media, Inc.", 2013.

Requirements for attendance (informal)

Courses

Requirements for attendance (formal)

None

References to Course [INF-71-63-K-6]

Module Name Context
[INF-71-63-M-6] Social Web Mining P: Obligatory 2V+1U, 4.0 LP
[SO-02-215-M-6] Knowledge management and technology WP: Obligation to choose 2V+1U, 4.0 LP
[SO-14-116--M-6] Application of intelligent systems WP: Obligation to choose 2V+1U, 4.0 LP
Course-Pool Name
[INF-KI_V-KPOOL-6] Lectures of the teaching area Intelligent Systems
[INF-SI_Inf_IntSys-KPOOL-7] Intelligent Systems