Overview

“Data mining, also called knowledge discovery in databases,  in computer science, is the process of discovering interesting and useful patterns and relationships in large volumes of data. The fieldcombines tools from statistics and artificial intelligence (such as neural networks and machine learning) with database management to analyze large digital collections, known as data sets. Data mining is widely used in business (insurance, banking, retail), science research (astronomy, medicine), and government security (detection of criminals and terrorists).”  Clifton, Christopher (2010). "Encyclopædia Britannica: Definition of Data Mining". Retrieved 2016-03-15.

Course content

• Introduction to Data Mining (DM) and Knowledge Discovery in Databases (KDD)
• Data preprocessing, feature selection, similarity and distance functions
• Frequent itemsets mining and association rules
• Classification
• Clustering
• Outlier detection

ECTS points: 4 (for ITIS students: 5)

Schedule

• Lecture: every Wednesday 14:00 - 15:30, starting from 12.04.2017
• Tutorials: directly after the lecture, 15:45-16:30
• Room: Multimedia-Hörsaal (3703 - 023), Appelstraße 4, 30167 Hannover

Teaching team

• Responsible Professor: Prof. Dr. Eirini Ntoutsi
• Assistance: Damianos Melidis, Tai Le Quy

Literature

• Tan/Steinbach/Kumar: Introduction to Data Mining; Pearson 2006.
• Han/Kamber: Data Mining - Concepts and Technques; 3rd ed., Morgan Kaufmann Publ., 201
• Witten/ Frank/Hall: Data Mining: Practical Machine Learning Tools and Techniques; 3rd ed., Morgan Kaufmann Publ., 2011.

Exam

• Written exam
• Friday 8.9.2017, 13.00-15.00,F102, F303,Welfengarten 1.

!!! Please check the Stud.IP page for announcements, material and up-to-date information on the course.