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master's thesis
Sustavi za preporučivanje zasnovani na suradničkom filtriranju
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:866606
Jukić, Nikolina
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Jukić, N. (2023). Sustavi za preporučivanje zasnovani na suradničkom filtriranju (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:866606

Jukić, Nikolina. "Sustavi za preporučivanje zasnovani na suradničkom filtriranju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:866606

Jukić, Nikolina. "Sustavi za preporučivanje zasnovani na suradničkom filtriranju." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:866606

Jukić, N. (2023). 'Sustavi za preporučivanje zasnovani na suradničkom filtriranju', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 21 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:866606

Jukić N. Sustavi za preporučivanje zasnovani na suradničkom filtriranju [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 June 21] Available at: https://urn.nsk.hr/urn:nbn:hr:168:866606

N. Jukić, "Sustavi za preporučivanje zasnovani na suradničkom filtriranju", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:866606

Metadata
TitleSustavi za preporučivanje zasnovani na suradničkom filtriranju
Title (english)Recommendation Systems Based on Collaborative Filtering
AuthorNikolina Jukić
MentorMarin Šilić (mentor)
Committee memberMarin Šilić (predsjednik povjerenstva)
Committee memberGoran Delač (član povjerenstva)
Committee memberKlemo Vladimir (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-04, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Širenjem internetskih tehnologija povećava se broj korisnika što uzrokuje rast dostupne količine informacija, odnosno dolazi do preopterećenja podatcima. Jedno od rješenja je razvoj sustava za preporučivanje. Opisane su vrste, svojstva i algoritmi sustava za preporučivanje s fokusom na sustave zasnovane na suradničkom filtriranju. Programski je ostvaren težinski hibridni sustav za preporučivanje koji koristi metodu k-najbližih susjeda i matričnu faktorizaciju. Provedeno je vrednovanje sustava na tri skupa podataka različitih veličina, ljestvica ocjena i informacija. Uspoređeni su rezultati pojedinačnih pristupa s hibridnim pristupom te je navedena korištena literatura.
Abstract (english)
With the rapid growth of Internet technologies number of users increases resulting in growth of available data and information overload. One solution is implementation of recommender systems. This thesis covers some types of recommender systems, their properties and algorithms they use, with focus on collaborative filtering methods. A weighted hybrid recommender system using k-nearest neighbors algorithm and matrix factorization was implemented. The evaluation of proposed recommender system was done on three different datasets, varying in dataset size, rating scale and type of information. Results of individual approaches were compared against the weighted hybrid approach.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:866606
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
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Created on2023-10-11 09:11:08