Hibridni sustav preporuke računalnih igara

master's thesis

• Title (english): Hybrid Video Game Recommender System
• Author: Anton Filipović
• Mentor: Goran Delač (mentor)
• Committee member: Goran Delač (predsjednik povjerenstva)
• Committee member: Marin Šilić (član povjerenstva)
• Committee member: Klemo Vladimir (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2020-07-07, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Cilj rada je opisati algoritme preporuke zasnovane na suradničkom filtriranju i algoritme zasnovane na sadržaju te hibridne pristupe koji kombiniraju opisane postupke. U radu se opisuju obilježja algoritama i prikazuje njihov princip rada nad pokaznim primjerima. Predstavljaju se postojeće metrike i eksperimenti za vrednovanje uspješnosti sustava preporučivanja. Za potrebe analize programskog rješenja prikupljen je prikladan skup podataka za preporuku računalnih igara korisnicima. Osmišljen je i programski ostvaren hibridni sustav preporuke koji primijenjuje pristupe zasnovane na sadržaju i suradničkom filtriranju. Provedeno je vrednovanje sustava preporuke nad primjerenim skupom podataka te je opisano programsko ostvarenje sustava i navedena korištena literatura i primljena pomoć.

Abstract (english)

The main goal of this master thesis is to describe recommender systems based on collaborative filtering and content based recommendation algorithms, as well as hybrid systems combining said approaches. Their characteristics and main principles are demonstrated on real world examples. Metrics and experiments for evaluation of system's accuracy are presented. Analysis of the recommendation system for video games is conducted on the collected dataset. Recommender system based on hybrid approach is developed and demonstrated showing collaborative filtering and content based principles.

• Keywords: Sustavi preporuke; suradničko filtriranje; filtriranje zasnovano na sadržaju; hibridni sustavi preporuke
• Keywords (english): Recommender Systems; collaborative filtering; content based filtering; hybrid recommender systems
• Language: croatian
• URN:NBN: urn:nbn:hr:168:700167
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-13 09:58:53