Recommendation systems and social networks Field of study: Computer Science
Programme code: W4-N2IN19.2021

Module name: Recommendation systems and social networks
Module code: W4-IN-N2-20-F-SRiSS
Programme code: W4-N2IN19.2021
Semester:
  • winter semester 2023/2024
  • summer semester 2022/2023
  • winter semester 2022/2023
  • summer semester 2021/2022
Language of instruction: Polish
Form of verification: course work
ECTS credits: 4
Description:
The aim of the module is to familiarize students with recommendation systems, their operating principles and algorithms associated with them. And with social networks and methods of their analysis.
Prerequisites:
(no information given)
Key reading:
1. Shlomo Berkovsky, Collaborative Recommendations, World Scientific 2. Neil Wilkins, Artificial Intelligence, 3. Charu C. Aggarwal, Recommender Systems: The Textbook 4. Neil CUNNINGTON, Social Media Algorithm
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
Has knowledge about the use and implementation of algorithms used in recommendation systems [M_001]
 K_W01 [1/5] K_W02 [1/5]
Has knowledge of the operation of recommendation systems and social networks. [M_002]
 K_W02 [1/5] K_W05 [1/5] K_W07 [1/5]
Can choose and implement the appropriate algorithm used in recommendation systems [M_003]
 K_U01 [1/5] K_U08 [1/5] K_U09 [1/5]
Is able to develop a scheme of dealing with data in recommendation systems, aimed at the proper operation of such a system. [M_004]
 K_U03 [1/5] K_U04 [1/5] K_U06 [1/5] K_U09 [1/5]
Is aware of raising their competences through continuous self-improvement [M_005]
 K_K01 [1/5] K_K02 [1/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Reports [W_001]
Preparation of written reports, their completion within a specified period as a verification of skills acquired during problem solving.
 M_001 M_002 M_003 M_004 M_005
Final test [W_002]
Test checking knowledge of the topics covered in lectures.
 M_001 M_002 M_005
Form of teaching Student's own work Assessment of the learning outcomes
Type Description (including teaching methods) Number of hours Description Number of hours
lecture [Z_001]
Lectures conducted using multimedia tools, discussing issues related to recommendation systems and social networks.
 15
Preparation for laboratories and passing the lecture.
 20 Final test [W_002]
laboratory classes [Z_002]
Preparing students to perform lab exercises. Practical presentation of issues discussed during lectures.
 30
Preparation for laboratory exercises. Self-solving laboratory exercises.
 55 Reports [W_001]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)