Sustavi za preporučivanje zasnovani na suradničkom filtriranju

master's thesis

• Title (english): Recommendation Systems Based on Collaborative Filtering
• Author: Andrea Krišto
• Mentor: Marin Šilić (mentor)
• Committee member: Marin Šilić (predsjednik povjerenstva)
• Committee member: Goran Delač (član povjerenstva)
• Committee member: Klemo Vladimir (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2024-07-04, Croatia

Abstract

Sustavi za preporučivanje korisnicima predlažu relevantne proizvode, usluge ili sadržaje
na temelju analize njihovih prethodnih aktivnosti i preferencija. U ovom radu
opisane su tri vrste sustava za preporučivanje te je implementiran sustav za preporučivanje
temeljen na suradničkom filtriranju na dva skupa podataka. Primjenom prikladno
odabranih mjera za vrednovanje ispitana je učinkovitost ostvarenog sustava te su grafički
prikazani rezultati opisivanja.

Abstract (english)

Recommendation systems suggest relevant products, services, or content to users
based on analysis of their past activities and preferences. This paper describes three
types of recommendation systems and implements a collaborative filtering-based recommendation
system on two datasets. The effectiveness of the implemented system was
evaluated using appropriately chosen metrics, and graphical representations of the results
are provided.

• Keywords: sustavi za preporučivanje; suradničko filtriranje; sustavi orijentirani prema korisniku
• Keywords (english): recommender systems; collaborative filtering; user-based filtering
• Language: croatian
• URN:NBN: urn:nbn:hr:168:286855
• 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: 2024-10-12 21:12:00