Web aplikacija za preporuku glazbe

undergraduate thesis

• Title (english): Web application for music recommendation
• Author: Franko Goričanec
• Mentor: Marina Bagić Babac (mentor)
• Committee member: Marina Bagić Babac (predsjednik povjerenstva)
• Committee member: Ljiljana Brkić (član povjerenstva)
• Committee member: Kristijan Poje (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2024-06-26, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Ovaj završni rad prikazuje razvoj aplikacije za preporuku glazbe koja predlaže pjesme na temelju korisnikovih preferiranih izvođača, uz pružanje informacija o općoj popularnosti pjesama koje korisnik sluša. Aplikacija se temelji na Spotify podacima. U prvom poglavlju istražuje se prikupljanje podataka i Spotify API te su objašnjeni Spotify atributi pjesama. Drugo poglavlje koristi prikupljene podatke kako bi se demonstrirali sustavi preporuka, posebice pristup temeljen na najbližem susjedu.... More Nadalje, daje se uvid u ograničenja sustava i prikupljanja podataka. Konačno, treće poglavlje istražuje stvaranje i dizajn web aplikacije za preporuku glazbe. Implementacija i važan kod su dani te objašnjeni. Less

Abstract (english)

This thesis presents a development of a music recommendation application that suggests songs based on the user's preferred artists, in addition to providing information on the general popularity of the songs the user listens to. The application is based on Spotify data. In the first chapter the data collection is explored and Spotify API, as well as song audio features are explained. The second chapter then uses the collected data to explore recommendation systems, specifically the nearest... More neighbour approach. Insight into limitations of the system and data collection is given. Finally, the third chapter explores the creation and design of the web application for music recommendation. The implementation and important code is given and explained. Less

• Keywords: Preporuke; Spotify; glazba; web aplikacija
• Keywords (english): Recommendations; Spotify; music; web application
• Language: english
• URN:NBN: urn:nbn:hr:168:734074
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2024-10-12 20:40:17