Universität Wien FIND

Due to the COVID-19 pandemic, changes to courses and exams may be necessary at short notice. Inform yourself about the current status on u:find and check your e-mails regularly. Registration is mandatory for courses and exams. Wearing a FFP2 face mask and a valid evidence of being tested, vaccinated or have recovered from an infection are mandatory on site.

Please read the information on studieren.univie.ac.at/en/info.

052414 VU Concepts and Models of Knowledge Engineering (2017W)

Continuous assessment of course work

Summary

1 Karagiannis , Moodle
2 Karagiannis , Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
Registration information is available for each group.

Groups

Group 1

max. 25 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

Attendance in the first lecture is mandatory.

Wednesday 04.10. 15:00 - 16:30 Seminarraum 7, Währinger Straße 29 1.OG
Wednesday 29.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 30.11. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Wednesday 06.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 07.12. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Wednesday 13.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 14.12. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 11.01. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Friday 12.01. 11:30 - 13:00 Hörsaal 1, Währinger Straße 29 1.UG
Wednesday 17.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 18.01. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Wednesday 24.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 25.01. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Monday 29.01. 13:15 - 14:45 Hörsaal 1, Währinger Straße 29 1.UG
Tuesday 30.01. 16:45 - 18:15 Hörsaal 2, Währinger Straße 29 2.OG
Wednesday 31.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 01.02. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG

Group 2

max. 25 participants
Language: English
LMS: Moodle

Lecturers

Classes (iCal) - next class is marked with N

Attendance in the first lecture is mandatory.

Wednesday 04.10. 08:00 - 09:30 Hörsaal 3, Währinger Straße 29 3.OG
Wednesday 29.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 30.11. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Wednesday 06.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 07.12. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Wednesday 13.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 14.12. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 11.01. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Friday 12.01. 11:30 - 13:00 Hörsaal 1, Währinger Straße 29 1.UG
Wednesday 17.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 18.01. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Wednesday 24.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 25.01. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG
Monday 29.01. 13:15 - 14:45 Hörsaal 1, Währinger Straße 29 1.UG
Tuesday 30.01. 16:45 - 18:15 Hörsaal 2, Währinger Straße 29 2.OG
Wednesday 31.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
Thursday 01.02. 09:45 - 11:15 Hörsaal 3, Währinger Straße 29 3.OG

Information

Aims, contents and method of the course

In this lecture, the goal is to gain expertise on the state of the art in knowledge engineering. Therefore, students explore the relevant theory and reinforce their knowledge in exercises. Knowledge engineering skills are applied on the topics "Factory of the Future", "Cyber-Physical Systems" and "Internet of Things".

Assessment and permitted materials

In the middle and at the end of the semester, a written test has to be passed. The test will contain theory questions and applied problems. During the test, no unauthorized materials are allowed and all electronic devices have to be turned off.

Until the end of the Semester, a project has to be completed. The project addresses Knowledge Engineering in the Domains "Factory of the Future", "Cyber-Physical Systems" and "Internet of Things". Thereby, a use case is conceptualized in a Design Phase, a solution is implemented in a Development Phase, and validation is performed in an Execution Phase.

In detail, the grade is constituted by:

* First Test 30 %
* Second Test 30%
* Project 40%

Missing class more than three times results in a negative grade.

Minimum requirements and assessment criteria

To receive a positive grade, 50 out of 100 percent are required. Grades are as follows:

* sehr gut (1) >= 87,00%
* gut (2) >= 75,00%
* befriedigend (3) >= 62,00%
* genügend (4) >= 50,00 %
* nicht genügend (5) < 50,00 %

Examination topics

Agent Systems
Constraint Satisfaction
Bayesian Scheme
Hidden Markov Models
Neural Networks I
Machine Learning
Neural Networks II
Evolutionary Computation
Genetic Algorithms
Semantic Web

Reading list

Script with lecture content
Moodle course

Dimitris Karagiannis, Rainer Telesko (2001), Wissensmanagement: Konzepte der künstlichen Intelligenz und des Softcomputing
Stuart J. Russell, Peter Norvig (2009), Artificial Intelligence - A Modern Approach

Association in the course directory

Module: WI2 KE

Last modified: Mo 07.09.2020 15:30