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Departments >> Faculty of Engineering >> Department of Computer Science >> Chair of Computer Science 6 (Data Management) >>

  Knowledge Discovery in Databases (KDD)

Lecturers
Dominik Probst, M. Sc., Melanie Bianca Sigl, M. Sc.

Details
Vorlesung
Online
2 cred.h
nur Fachstudium, Sprache Englisch
Zeit: Mon 10:15 - 11:45, Zoom-Meeting

Fields of study
WPF INF-MA ab 2
WPF INF-LAG 4-6
WPF INF-LAR 4-6
WPF INF-BA 4-6
WF M-BA 4-6
WPF DS-BA ab 3
WPF DS-MA ab 1
WPF IIS-MA 2-3
WF MT-MA-BDV ab 1

Prerequisites / Organisational information
  • Konzeptionelle Modellierung

Contents
1. Introduction
2. Data
3. Preprocessing
4. Data Warehousing and Online Analytical Processing
5. Mining Frequent Patterns, Associations and Correlations
6. Classification
7. Cluster Analysis
8. Outlier Analysis

Recommended literature
The lecture is based on the following book:
  • J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques, 3rd. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2011, ISBN: 0123814790

Also interesting and related textbooks are:

  • A. Géron, Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems, 2nd ed. O’Reilly Media, 2017, ISBN: 978-1491962299

  • H. Du, Data Mining Techniques and Applications: An Introduction. Cengage Learning EMEA, May 2010, p. 336, ISBN: 978-1844808915

  • I. H. Witten, E. Frank, M. A. Hall, et al., Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques, 4th. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2016, ISBN: 0128042915

ECTS information:
Title:
Knowledge Discovery in Databases

Prerequisites
  • Conceptual Modeling

Contents
1. Introduction
2. Data
3. Preprocessing
4. Data Warehousing and Online Analytical Processing
5. Mining Frequent Patterns, Associations and Correlations
6. Classification
7. Cluster Analysis
8. Outlier Analysis

The students will learn about:

  • the particular challenges of data mining on large sets of data

  • the technologies available for data analysis

  • the process of data mining

  • applications

Literature
  • Han, Jiawei ; Kamber, Micheline ; Pei, Jian: Data Mining: Concepts and Techniques. 3rd ed. Waltham, MA : Morgan Kaufmann, 2012 (The Morgan Kaufmann Series in Data Management Systems). - ISBN 978-0-12-381479-1 (copies are available in the TNZB)
  • Du, Hongbo: Data Mining Techniques and Applications. Andover, UK : Cengage Learning, 2010

  • Witten, Ian H. ; Frank, Eibe ; Hall, Mark A.: Data Mining. Practical Machine Learning Tools and Techniques. 3rd ed. Burlington, MA : Morgan Kaufmann, 2011 (The Morgan Kaufmann Series in Data Management Systems). - ISBN 978-0-12-3748569-0

Additional information
Keywords: Data Mining, KDD
Expected participants: 200

Assigned to: Übungen zu KDD

Verwendung in folgenden UnivIS-Modulen
Startsemester SS 2022:
Knowledge Discovery in Databases (KDD)
Knowledge Discovery in Databases mit Übung (KDDmUe)

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