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undergraduate thesis
Ostvarenje sustava preporučivanja koristeći algoritam suradničkog filtriranja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:792415
Bago, Lucija
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Bago, L. (2021). Ostvarenje sustava preporučivanja koristeći algoritam suradničkog filtriranja (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:792415

Bago, Lucija. "Ostvarenje sustava preporučivanja koristeći algoritam suradničkog filtriranja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:792415

Bago, Lucija. "Ostvarenje sustava preporučivanja koristeći algoritam suradničkog filtriranja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:792415

Bago, L. (2021). 'Ostvarenje sustava preporučivanja koristeći algoritam suradničkog filtriranja', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 04 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:792415

Bago L. Ostvarenje sustava preporučivanja koristeći algoritam suradničkog filtriranja [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 July 04] Available at: https://urn.nsk.hr/urn:nbn:hr:168:792415

L. Bago, "Ostvarenje sustava preporučivanja koristeći algoritam suradničkog filtriranja", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:792415

Metadata
TitleOstvarenje sustava preporučivanja koristeći algoritam suradničkog filtriranja
Title (english)Recommendation Systems Implementation Using Collaborative Filtering Algorithm
AuthorLucija Bago
MentorKlemo Vladimir (mentor)
Committee memberKlemo Vladimir (predsjednik povjerenstva)
Committee memberAdrian Satja Kurdija (član povjerenstva)
Committee memberLucija Šikić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-09-07, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
„A lot of times, people don’t know what they want until you show it to them“ ili u prijevodu „Ljudi često ne znaju što žele dok im to ne pokažeš“, citat je Stevea Jobsa koji savršeno opisuje ulogu sustava preporučivanja. Sustavi preporučivanja igraju veliku ulogu u današnjem svijetu, olakšavajući pristup brojnim sadržajima, produktima i uslugama koje ne bismo sami lako pronašli. Zaslužni su za individualne preporuke u moru različitih ponuda, pritom ne zatrpavajući korisnika beskorisnim informacijama već održavajući savršenu ravnotežu onoga što se nudi i onoga što pojedinom korisniku treba. Formalnije, sustavi preporučivanja su algoritmi koji služe za predlaganje sadržaja korisnicima na temelju njihovih prethodnih pretraživanja, njihovih afiniteta, opredjeljenja i stavova ili na temelju sličnosti s drugim korisnicima. Postoje dvije osnovne vrste sustava preporučivanja, oni temeljeni na sadržaju i oni temeljeni na suradničkom filtriranju.
Abstract (english)
As Steve Jobs once said, „A lot of times, people don’t know what they want until you show it to them“. The quote describes the role of recommender systems flawlessly. Recommender systems have an extremely important role nowadays, facilitating access to the enormous amount of content, products, and services we wouldn't have found ourselves otherwise. They take credit for individual recommendations in a sea of diverse offers, perfectly balancing what is out there and what the user needs without overwhelming them with useless information. To be more formal, recommender systems are algorithms used to recommend content to users based on their previous searches, their preferences, orientation, perspectives, affiliations, or based on the similarity with other users. There are two main types of recommender systems, ones that are content-based and collaborative filtering recommender systems.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:792415
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 on2023-01-15 09:42:55