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undergraduate thesis
Sustav za preporuku filmova
2023. urn:nbn:hr:168:112593
Špehar, Nikolina
University of Zagreb
Faculty of Electrical Engineering and Computing

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Špehar, N. (2023). Sustav za preporuku filmova (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:112593

Špehar, Nikolina. "Sustav za preporuku filmova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:112593

Špehar, Nikolina. "Sustav za preporuku filmova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:112593

Špehar, N. (2023). 'Sustav za preporuku filmova', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 12 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:112593

Špehar N. Sustav za preporuku filmova [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 July 12] Available at: https://urn.nsk.hr/urn:nbn:hr:168:112593

N. Špehar, "Sustav za preporuku filmova", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:112593

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Metadata
TitleSustav za preporuku filmova
Title (english)System for movie recommendation
AuthorNikolina Špehar
MentorMarko Đurasević (mentor)
Committee memberMarko Đurasević (predsjednik povjerenstva)
Committee memberNikolina Frid (član povjerenstva)
Committee memberJosip Šarić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Sustavi za preporuku su područje strojnog učenja, koje nam pomaže pri radu s ogromnim količinama podataka s kojom smo u današnje doba zatrpani. Ovaj rad bavi se implementacijom sustava za preporuku filmova. Implementirane su tri različite vrste sustava za preporuku; kolaborativno filtriranje, filtriranje po sadržaju i spoj te dvije vrste. Pokazano je da kolaborativno filtriranje i filtriranje po sadržaju daju relativno slične preporuke. Dok implementacija preporuke povezivanjem te dvije vrste daje nepovezane preporuke.
Abstract (english)
Recommendation systems are a field of machine learning, which helps us work with the huge amounts of data we are overwhelmed whit today. This paper deals with the implementation of a movie recommendation system. Three different types of recommendation systems have been implemented; collaborative filtering, content based filtering and a combination of the two types. It has been shown that collaborative filtering and content based filtering provide similar recommendations. While implementation of recommendation system, which is based on connecting collaborative and content based filtering, gives unrelated recommendations.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:112593
Study programmeTitle: 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 resourceText
File originBorn digital
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Created on2023-10-11 10:41:36