Web aplikacija za preporuku filmova

undergraduate thesis

• Title (english): Web application for movie recommendations
• Author: Neven Marciuš
• 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: 2023-07-11, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Cilj ovog rada je dizajnirati i razviti web aplikaciju koja koristi sustav preporuka za sugeriranje filmova korisnicima na temelju njihovih preferencija. Skup podataka MovieLens koristit će se za obuku sustava preporuka i primjenu pristupa kolaborativnog filtriranja. Razvijena web aplikacija imat će intuitivno korisničko sučelje koje korisnicima omogućuje davanje povratnih informacija o predloženim filmovima, što će sustavu omogućiti da s vremenom poboljša svoje preporuke. U radu će se također istražiti mogućnost uključivanja dodatnih izvora podataka, kao što su ocjene filmova i recenzije s platformi društvenih medija, kako bi se povećala točnost sustava preporuka.

Abstract (english)

The objective of this thesis is to design and develop a web application that utilizes a recommendation system to suggest movies to users based on their preferences. The MovieLens dataset will be used to train the recommendation system and apply the collaborative filtering approach. The developed web application will offer an intuitive user interface that allows users to provide feedback on the suggested movies, which will enable the system to improve its recommendations over time. The thesis will also explore the possibility of incorporating additional data sources, such as movie ratings and reviews from social media platforms, to enhance the accuracy of the recommendation system.

• Keywords: {Strojno učenje; Sustavi preporuka; Kolaborativno filtriranje; Singular Value Decomposition; Web aplikacija
• Keywords (english): Mahcine learning; Recommendation systems; Collaborative filtering; Singular Value Decomposition; Web application
• Language: english
• URN:NBN: urn:nbn:hr:168:132925
• 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: Closed access
• Created on: 2023-10-11 09:39:42