FI:P056 Knowledge Discovery in Databas - Course Information
P056 Knowledge Discovery in Databases
Faculty of InformaticsSpring 1998
- 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
- Teacher's information
- http://www.fi.muni.cz/usr/popelinsky/lectures/kdd/
- Enrolment Statistics (Spring 1998, recent)
- Permalink: https://is.muni.cz/course/fi/spring1998/P056