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master's thesis
Web-aplikacija za preporuku filmova
2022. urn:nbn:hr:168:032651
Bikić, Lovro
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Bikić, L. (2022). Web-aplikacija za preporuku filmova (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:032651

Bikić, Lovro. "Web-aplikacija za preporuku filmova." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:032651

Bikić, Lovro. "Web-aplikacija za preporuku filmova." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:032651

Bikić, L. (2022). 'Web-aplikacija za preporuku filmova', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 12 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:032651

Bikić L. Web-aplikacija za preporuku filmova [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 November 12] Available at: https://urn.nsk.hr/urn:nbn:hr:168:032651

L. Bikić, "Web-aplikacija za preporuku filmova", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:032651

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Metadata
TitleWeb-aplikacija za preporuku filmova
Title (english)Movie Recommender Web Application
AuthorLovro Bikić
MentorIgor Mekterović (mentor)
Committee memberIgor Mekterović (predsjednik povjerenstva)
Committee memberLjiljana Brkić (član povjerenstva)
Committee memberSlaven Zakošek (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-11, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovome radu teoretski su istraženi algoritmi (filtriranje na temelju sadržaja, kolaborativno filtriranje, hibridni algoritmi) i učestali problemi (npr. cold start) sustava za preporučivanje koristeći postojeću literaturu. Istraženi teoretski principi primijenjeni su za razvoj web-aplikacije za preporuku filmova koja nudi nepersonalizirane preporuke za sve korisnike, personalizirane preporuke za prijavljene korisnike, te preporuke za pojedine filmove. Kvaliteta implementiranih preporuka ispitana je javnim upitnikom i statističkim metodama, koji su dali zadovoljavajuće rezultate.
Abstract (english)
In this thesis, recommender algorithms (content-based filtering, collaborative filtering, hybrid algorithms) and common problems surrounding them (e.g. cold start) have been researched by looking at existing literature. The researched theoretical principles were then applied to the development of a movie recommendation web-application which offers non-personalized recommendations to all users, personalized recommendations to registered users, and recommendations for individual movies. Quality of the implemented algorithms was verified via statistical methods and a public questionnaire, which gave satisfactory results.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:032651
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
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Created on2023-01-13 14:33:50