Course: Data mining methods

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Course title Data mining methods
Course code ITE/MVD
Organizational form of instruction Lecture + Lesson
Level of course Bachelor
Year of study not specified
Semester Winter
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements Course does not contain work placement
Recommended optional programme components None
Lecturer(s)
  • Červa Petr, doc. Ing. Ph.D.
  • Šafařík Radek, Ing.
  • Žďánský Jindřich, Ing. Ph.D.
  • Kynych František, Ing.
Course content
Lecture topics: 1. Introduction and data visualization 2. Analysis and text datamining 3. Vector model, TF transformation 4. Text extraction systems 5. Probabilistic and statistical extractive models 6. Feedback for text extraction, web search 7. Evaluation of documents, recommender systems 8. Natural language analysis 9. Syntagmatic relations 10. Analysis of the topic 11. Clustering and categorization of text 12. Sentiment analysis 13. Contextual extraction 14. Pattern search

Learning activities and teaching methods
Monological explanation (lecture, presentation,briefing), Self-study (text study, reading, problematic tasks, practical tasks, experiments, research, written assignments)
Learning outcomes
Prerequisites
unspecified

Assessment methods and criteria
Combined examination

Recommended literature
  • BERKA, Petr. Dobývání znalostí z databází. 2003. ISBN 80-200-1062-.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester