FI:P056 Knowledge Discovery in Databas - Course Information

P056 Knowledge Discovery in Databases

Extent and Intensity

2/0. 2 credit(s). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).

Teacher(s)

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

Guaranteed by

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

• Date warehousing, OLAP, ROLAP.
• Knowledge, association, dependency in databases. Interestingness relation. Knowledge discovery in databases(KDD). Data mining.
• Typical KDD tasks: clustering, classification, dependency discovery, deviation detection.
• Introduction to knowledge discovery algorithms: Machine learning. Statistics.
• DBMS extension to support KDD. KESO Project.
• Inductive query languages. DBLearn.
• Knowledge discovery in RDB, OODB, and WWW.
• KDD systems: C4.5, CLEMENTINE, ECCE.

Language of instruction

Czech

Further comments (probably available only in Czech)

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 1999, recent)
  
• Permalink: https://is.muni.cz/course/fi/spring1999/P056