Decision Support Systems
| Code | Completion | Credits | Range | Language |
|---|---|---|---|---|
| NI-DSS | Z,ZK | 5 | 2P+1C | Czech |
- Garant předmětu:
- Robert Pergl
- Lecturer:
- David Buchtela, Petra Pavlíčková, Robert Pergl
- Tutor:
- David Buchtela, Petra Pavlíčková
- Supervisor:
- Department of Software Engineering
- Synopsis:
-
The aim of the course is to provide students with knowledge and skills in decision support systems, their classification (Powerova), selected principles of data-oriented, model-oriented and knowledge-oriented decision support systems. Students will also gain knowledge of multicriterial decision-making methods and game theory. They will also learn about the principles of conceptually and ontologically oriented decision support systems and the basics of distribution, optimization and evolution methods and algorithms.
- Requirements:
-
No special entry requirements are required to complete the course.
- Syllabus of lectures:
-
1. Principles of decision support systems, Power classification, decision process and its phases.
2. Decision theory (under certainty, uncertainty, risk), multi-criteria decision making.
3. Game theory and decision models.
4. Executive IS, expert systems, systems for group decision support.
5. Operational research support systems: optimization and distribution methods, evolutionary algorithms.
6. Risk management and risk management support systems.
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7. Expert and knowledge systems. Diagnostic and generative systems. Knowledge representation methods.
8. Inference mechanism - backward and forward chaining. Processing uncertainty in knowledge systems. Explanation module.
9. Knowledge ontology. KADS methodology. Conceptual ontological modeling - OntoUML, GLIKREM.
10. Data-oriented decision support systems. Business Intelligence (BI) systems. Data Warehouses - Star and Snowflake Schema.
11. Document and web-oriented systems. Communication-oriented systems - Groupware.
12. Geographic-oriented systems - GIS and layered access to data. Knowledge and strategy maps.
13. Knowledge mining from databases and free texts - analytical methods, 5A methodology, SEMMA and CRISP-DM. Life cycle of knowledge.
- Syllabus of tutorials:
-
1. Principles of decision support systems, Power classification, decision process and its phases.
2. Decision theory (under certainty, uncertainty, risk), multi-criteria decision making.
3. Game theory and decision models.
4. Executive IS, expert systems, systems for group decision support.
5. Operational research support systems: optimization and distribution methods, evolutionary algorithms.
6. Risk management and risk management support systems.
---
7. Expert and knowledge systems. Diagnostic and generative systems. Knowledge representation methods.
8. Inference mechanism - backward and forward chaining. Processing uncertainty in knowledge systems. Explanation module.
9. Knowledge ontology. KADS methodology. Conceptual ontological modeling - OntoUML, GLIKREM.
10. Data-oriented decision support systems. Business Intelligence (BI) systems. Data Warehouses - Star and Snowflake Schema.
11. Document and web-oriented systems. Communication-oriented systems - Groupware.
12. Geographic-oriented systems - GIS and layered access to data. Knowledge and strategy maps.
13. Knowledge mining from databases and free texts - analytical methods, 5A methodology, SEMMA and CRISP-DM. Life cycle of knowledge.
- Study Objective:
-
The aim of the course is to provide students with knowledge and skills in decision support systems, their classification (Powerova), selected principles of data-oriented, model-oriented and knowledge-oriented decision support systems. Students will also gain knowledge of multicriterial decision-making methods and game theory.
- Study materials:
-
1. Burstein, F. : Handbook on Decision Support Systems 1: Basic Themes. Springer, 2008. ISBN 978-3-540-48712-8.
2. Burstein, F. : Handbook on Decision Support Systems 2: Variations. Springer, 2008. ISBN 978-3-540-48715-9.
3. Clyde W. Holsapple, Andrew B. Whinston : Decision support systems: a knowledge-based approach. West Group, 1996. ISBN 978-0314065100.
4. David Schuff, David Paradice : Decision Support: An Examination of the DSS Discipline. Springer, 2010. ISBN 978-1-4419-6180-8.
- Note:
- Further information:
- https://moodle-vyuka.cvut.cz/link/course.php?cx=NI-DSS
- Time-table for winter semester 2024/2025:
-
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon Tue Wed Thu Fri - Time-table for summer semester 2024/2025:
- Time-table is not available yet
- The course is a part of the following study plans:
-
- Master specialization Computer Science, in Czech, 2018-2019 (elective course)
- Master specialization Computer Security, in Czech, 2020 (elective course)
- Master specialization Design and Programming of Embedded Systems, in Czech, 2020 (elective course)
- Master specialization Computer Systems and Networks, in Czech, 202 (elective course)
- Master specialization Management Informatics, in Czech, 2020 (PS)
- Master specialization Software Engineering, in Czech, 2020 (compulsory elective course, elective course)
- Master specialization System Programming, in Czech, version from 2020 (elective course)
- Master specialization Web Engineering, in Czech, 2020 (elective course)
- Master specialization Knowledge Engineering, in Czech, 2020 (elective course)
- Master specialization Computer Science, in Czech, 2020 (elective course)
- Mgr. programme, for the phase of study without specialisation, ver. for 2020 and higher (VO)
- Master Specialization Digital Business Engineering, 2023 (VO)
- Master specialization System Programming, in Czech, version from 2023 (elective course)
- Master specialization Computer Science, in Czech, 2023 (elective course)