FI:P056 Knowledge discovery in DB - Course Information

P056 Knowledge Discovery in Databases

Extent and Intensity

2/1. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).

Teacher(s)

doc. RNDr. Lubomír Popelínský, Ph.D. (lecturer)

Guaranteed by

prof. RNDr. Mojmír Křetínský, CSc.
Department of Computer Science – Faculty of Informatics
Contact Person: doc. RNDr. Lubomír Popelínský, Ph.D.

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.

fields of study / plans the course is directly associated with

• Informatics (programme FI, B-IN)
• Informatics (programme FI, M-IN)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-IN)
• Upper Secondary School Teacher Training in Informatics (programme FI, M-SS)
• Information Technology (programme FI, B-IN)

Syllabus

• Knowledge, association, dependency in databases. Interestingness relation. Knowledge discovery in databases(KDD). Data mining.
• Typical KDD tasks: clustering, classification, dependency discovery, deviation detection.
• Basci algorithms of machine learning.
• DBMS extension to support KDD. KESO Project.
• Inductive query languages. DBLearn.
• Knowledge discovery in RDB, OODB, geographic data and WWW and text.
• Data warehousing, OLAP.

Literature

• Advances in knowledge discovery and data mining. Online. Edited by Usama M. Fayyad. Menlo Park: AAAI Press, 1996. xiv, 611. ISBN 0262560976. [citováno 2024-04-24] info

Assessment methods (in Czech)

Nutnou podmínkou absolvování je projekt.

Language of instruction

Czech

Further Comments

The course is taught annually.
The course is taught: every week.

Teacher's information

http://www.fi.muni.cz/usr/popelinsky/lectures/kdd/

• Enrolment Statistics (Spring 2000, recent)
  
• Permalink: https://is.muni.cz/course/fi/spring2000/P056