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Knowledge Discovery in Databases II (SS 2019)

News

  • Klausurtermin: 02.08.2019, 17-19 Uhr. Please register through UniWorX
  • This week we only give an introduction to this course. The next week lecture will be canceled due to the holiday. Thus, our tutorial will start at 13.05.2019.
  • Lecture on 05.Jun.2017 is canceled. So no tutorial next week.
  • The tutorial is canceled for this week (24/25.06.19).  Ex6 will be discussed together with ex7 next week.
  • Final exam: 02.08.2019, 17:00-19:00, Geschw.-Scholl-Pl. 1 (B) - B 101
  • There will be no tutorial on Sequence Data Section 4 (Trajectories). Only basic concepts (the five basic trajectory patterns) will be covered in the final exam.

Organization

  • Umfang: 3+2 Semesterwochenstunden
  • Required: Lecture "Knowledge Discovery in Databases I" or equivalent
  • ECTS: 6

 

Time and Locations

Component When Where Starts at
Lecture Wed, 9,00 - 12,00 h Room B 001 (Oettingenstr. 67) 24.04.2019
Tutorial 1 Mon, 14,00 - 16,00 h Room M 001 (HGB) 29.04.2019
Tutorial 2 Mon, 16,00 - 18,00 h Room M 001 (HGB) 29.04.2019
Tutorial 3 Tue, 14,00 - 16,00 h Room A 022 (HGB) 30.04.2019
Tutorial 4 Tue, 16,00 - 18,00 h  Room A 022 (HGB) 30.04.2019

Time and Locations

LectureTutorial
DateTopicDateExerciseMaterial
24.04.19 Introduction
08.05.19 High Dimensional Data 1 (Section 1-2) 13/14.05.19 ex1
15.05.19 High Dimensional Data 2 (Section 3) 20/21.05.19 ex2
22.05.19 High Dimensional Data 3 (Section 4) 27/28.05.19 ex3
29.05.19 High Dimensional Data 4 (Section 5. and 5.2) 03/04.06.19 ex4
12.06.19 High Dimensional Data 5 (Section 5.3,5.4) 17/18.06.19 ex5
19.06.19 High Dimensional Data 5 (Section 5.5)
Data Streams (Section 1)
24/25.06.19 ex6 material
26.06.19 Data Streams (Section 2) 01/02.07.19 ex7
03.07.19 Data Streams (Section 3) 08/09.07.19 ex8
10.07.19 Sequence Data (Section 1-2) 15/16.07.49 ex9
17.07.19 Sequence Data (Section 3) 22/23.07.19 ex10
24.07.19 Sequence Data (Section 4)


Content

In many modern application areas, data scientists face challenges which go beyond the basic techniques being introduced in the basic module Knowledge Discovery in Databases I. The module Knowledge Discovery in Databases II covers advanced techniques to handle large data volumes, volatile data streams, complex object descriptions and linked data. These topics are also known as the three major challenges (Volume, Velocity, Variety) in Big Data Analysis. The module is directed at master students being interested in developing and designing knowledge discovery processes for various types of applications. This includes the development of new data mining and data preprocessing methods as well as the ability to select the best suited established approach for a given practical challenge.

 

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