Web search systems

1.

Subject title

Web search systems

Веб пребарувачки системи

2.

Code

F23L3S080

3.

Study program

Примена на информациски технологии, Софтверско инженерство и информациски системи, Компјутерски науки, Компјутерско инженерство, Интернет, мрежи и безбедност, Информатичка едукација, Software engineering and information systems, Примена на информациски технологии, Софтверско инженерство и информациски системи, Компјутерски науки, Компјутерско инженерство, Интернет, мрежи и безбедност, Software engineering and information systems, Стручни студии за програмирање, Стручни студии за програмирање,

4.

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

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Прв циклус

6.

Academic year / semester

4 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

ворн. проф. д-р Иван Китановски проф. д-р Ивица Димитровски

9.

Prerequisites for enrollment

Вештачка интелигенција или Вовед во науката за податоци или Машинско учење

10.

Subject goals and competencies:

Familiarity with concepts for the development of web search systems. Understanding of query processing methods and searchable document sets, as well as ways to automatically collect data from the web. After completing the course, the student is expected to demonstrate knowledge of query processing methods, document representation and their indexing and classification, to demonstrate knowledge of image search and indexing methods, and to be able to independently develop search algorithms using software tools.

11.

Subject content:

Lectures: 1. Introduction to web search systems. 2. Processing of questions; Backlink search. 3. Vector spaces; Structure of documents; Creating indexes. 4. Evaluation of search systems. 5. Clustering and classification of documents. 6. Collecting information from web and social networks and indexing them. 7. Personalized search. 8. Algorithms for answering questions. 9. Image Search and Indexing. 10. Image Search and Indexing. 11. Ethical challenges in information search: privacy, detection of fake news, fair search. 12. Language models with neural networks and vector representation. Exercises: 1. Overview of libraries and search tools. ElasticSearch Overview. 2. Query processing with ElasticSearch and Python. 3. Data Indexing with ElasticSearch and Python. 4. Overview of evaluation metrics. 5. Implementation of document clustering and classification algorithms in Python. 6. Implementing a data fetching bot in Python. 7. Implementation of personalized search algorithms in Python. 8. Implementation of algorithms for understanding and answering questions in Python. 9. Implementation of image indexing and search algorithms. 10. Implementation of image indexing and search algorithms. 11. Overview of Fake News Detection Models, Fair Search. 12. Overview of models based on neural networks and different vector representations in the context of information retrieval.

12.

Learning methods:

Предавања со користење на презентации, 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.

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

30 + 45 + 15 + 15 + 75 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

30 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

45 hours

16.

Other forms of activities

16.1.

Project tasks

15 hours

16.2.

Independent tasks

15 hours

16.3.

Homework

75 hours

17.

Grading method

17.1.

Tests

0 points

17.2.

Seminar work / project (presentation: written and oral)

15 points

17.3.

Activities and learning

0 points

17.4.

Final exam

70 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 актибвности 15.2 и 16.1

20.

Language of instruction

Македонски и англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature