Staff members

Teaching courses etc.
Further material
Teaching overview (PDF)
Teaching cycle

Diploma-, master and bachelor theses

Projects

Publications and searching for literature

About us (Contact address, travel information, history)

Jobs in our group

Department

Promotionsausschuss Abteilung Informatik

FGIR (German Informatics Society (GI) specialist group on Information Retrieval)

International Journal on Digital Libraries

CONTACT
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INTERNAL

DEUTSCH

Data Mining - Lecture, Winter 2005/2006

Teaching personnel

Lecturer

Prof. Dr.-Ing. Norbert Fuhr

Formalia

Targeted audience

DAI Hauptstudium with 4 credit points : Bereich "D"
ISE Master with 4 credit points

Dates

Lectures

Date	Time	Place
Mittwoch	14:15 - 15:45	LF/052

Description

Data mining deals with the extraction of implicit, yet unknown knowledge from raw data. For this purpose, there are methods for analyzing databases, in order to identify patterns and to perform abstraction, in order to produce valuable knowledge. The methods applied are based on machine techniques.

Course structure:

Input: Concepts, Instances, Attributes
Output: Knowledge Representation
Algorithms: The Basic Methods
Credibility: Evaluating What's Been Learned
Implementations: Real Machine Learning Schemes
Moving On: Engineering the Input and Output
Nuts And Bolts: Machine Learning Algorithms In Java

Slides

The slides and other background material can be found here.

Mitschriften

Assignments / preparation for the oral exam

Examples for assignments can be found here.
Examples for questions in the oral exam (only in German)
(consider also the repetition slides)

Additional material

The course is based on the book `Data Mining' by Ian Witten und Eibe Frank