Course details
Knowledge Discovery in Databases
Guarantor
Language of instruction
Czech, English
Completion
Examination
Time span
- 39 hrs lectures
- 13 hrs projects
Department
Study literature
- Bishop, CH. M.: Pattern Recognition and Machine Learning. Springer, 2006, 738 p. ISBN 978-0-387-31073-2.
- Aggarwal, Ch.C. (ed.): Data Streams: Models and Algorithms. Advances in Database Systems. Springer, 2006, 358 p. ISBN 0387287590.
- Příspěvky v dostupných časopisech a sbornících konferencí (včetně dostupných v ACM Digital library, IEEE Digital library a jiných elektronických zdrojích).
Fundamental literature
- Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Third Edition. Elsevier Inc., 2012, 703 p. ISBN 978-0-12-381479-1.
- Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Second Edition. Elsevier Inc., 2006, 770 p. ISBN 1-55860-901-3.
Syllabus of lectures
- Data preprocessing.
- Data warehousing.
- Asociation analysis.
- Classification and prediction.
- Cluster analysis.
- Advanced data mining in 'classic' data sources.
- Mining in data streams.
- Data mining in time series and sequences.
- Mining in biological data.
- Data mining in graph structures.
- Multirelational data mining.
- Mining in object, spatial and multimedia data.
- Text mining and Web mining.
Course inclusion in study plans