Knowledge-based information systems

Knowledge-based information systems

1.

Subject title

Knowledge-based information systems

Информациски системи базирани на знаење

2.

Code

m23_s_007

3.

Study program

Cloud Computing, Data science in computer science and engineering, Bioinformatics, Security, Cryptography and Coding, Еducation with ICT, Eco-informatics, Internet Technologies and cyber security, Computer Science, Software for embedded systems, Software Engineering, Cloud Computing, Bioinformatics, Security, Cryptography and Coding, Statistics and Data Analytics, IT management, Statistics and Data Analytics, IT management, Software Engineering, Inteligent Systems,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Кире Триводалиев проф. д-р Слободан Калајџиски

9.

Prerequisites for enrollment

10.

Subject goals and competencies:


The student will be capable of modeling and developing information systems based on Knowledge through the use of modern knowledge detection tools.

11.

Subject content:


Databases and bases of knowledge. Contemporary data analysis and search tools (indexing and searching, distributed and parallel processing, web search engines, recommendation systems). Data warehouses and decision -making systems. Analytical processing and data mining in data warehouses. Knowledge Discovery Detection Processes (Knowledge Discovery in Databases - KDD) Technologies: Selection, Data Cleaning (Processing, Transformation), Interpretation/Evaluation. Detecting knowledge in huge amounts of data (big data).

12.

Learning methods:


Предавања поддржани со презентации преку слајдови, интерактивни предавања, вежби (користење на опрема и софтверски пакети), тимска работа, пример случаи, поканети гости предавачи, самостојна изработка и одбрана на проектна задача и семинарска работа, учење во електронско опкружување (форуми, консултации).

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

60 + 0 + 45 + 45 + 30 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

60 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

0 hours

16.

Other forms of activities

16.1.

Project tasks

45 hours

16.2.

Independent tasks

45 hours

16.3.

Homework

30 hours

17.

Grading method

17.1.

Tests

15 points

17.2.

Seminar work / project (presentation: written and oral)

45 points

17.3.

Activities and learning

15 points

17.4.

Final exam

0 points

18.

Grading criteria (points / grade)

up to 50 points

5 (five) (F)

from 51 to 60 points

6 (six) (E)

from 61 to 70 points

7 (seven) (D)

from 71 to 80 points

8 (eight) (C)

from 81 to 90 points

9 (nine) (B)

from 91 to 100 points

10 (ten) (A)

19.

Condition for signature and taking final exam

реализирани активности 15.1 и 15.2

20.

Language of instruction

македонски и англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

No.

Author

Title

Publisher

Year

6497

E. Turban, J. E. Aronson, T-P. Liang, R. Sharda

Decision Support and Business Intelligence Systems

Prentice Hall

2006

6498

D.A. Grossman, O. Frieder

Information retrieval (Algorithms and Heuristics)

Springer

1998

6499

S. Büttcher,‎ C. L. A. Clarke,‎ G. V. Cormack

Information Retrieval: Implementing and Evaluating Search Engines

MIT Press

2016

6500

Steven S. Skiena

The Data Science Design Manual

Springer

2017

6501

Charu C. Aggarwal

Recommender Systems: The Textbook

Springer

2016

22.2.

Additional literature

No.

Author

Title

Publisher

Year