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. Edited by Usama M. Fayyad. Menlo Park: AAAI Press, 1996, xiv, 611. ISBN 0262560976. 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