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master's thesis
Sustav za generiranje preporuka temeljen na analizi javno dostupnih podataka
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. urn:nbn:hr:168:746607
Antolić, Goran
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Antolić, G. (2017). Sustav za generiranje preporuka temeljen na analizi javno dostupnih podataka (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:746607

Antolić, Goran. "Sustav za generiranje preporuka temeljen na analizi javno dostupnih podataka." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:746607

Antolić, Goran. "Sustav za generiranje preporuka temeljen na analizi javno dostupnih podataka." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:746607

Antolić, G. (2017). 'Sustav za generiranje preporuka temeljen na analizi javno dostupnih podataka', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 20 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:746607

Antolić G. Sustav za generiranje preporuka temeljen na analizi javno dostupnih podataka [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2017 [cited 2024 June 20] Available at: https://urn.nsk.hr/urn:nbn:hr:168:746607

G. Antolić, "Sustav za generiranje preporuka temeljen na analizi javno dostupnih podataka", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:168:746607

Metadata
TitleSustav za generiranje preporuka temeljen na analizi javno dostupnih podataka
Title (english)Recommender System Based on the Publicly Available Data
AuthorGoran Antolić
MentorLjiljana Brkić (mentor)
Committee memberLjiljana Brkić (predsjednik povjerenstva)
Committee memberBoris Vrdoljak (član povjerenstva)
Committee memberIgor Mekterović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2017-02-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Ovaj rad opisuje dizajn i razvoj preporučiteljskog sustava koji gradi profil korisnika na temelju podataka preuzetih s društvenih mreža. Ti podaci sadrže informacije o korisnikovim interesima i služe kako bi se svladao čest problem preporučiteljskih sustava zvan cold start. Izgrađeni korisnički profil koristi se kod pretraživanja sadržaja koji bi korisniku mogao biti relevantan. Preporučiteljski sustavi uobičajeno su vezani samo uz jednu domenu, dok se u ovom radu opisuje arhitektura sustava koja podržava preporučivanje sadržaja iz različitih domena. U web-aplikaciji korisniku se preporučuju filmovi, glazbeni izvođači i web-članci. Kako bi se za korisnika u budućnosti mogle generirati bolje preporuke, razvijen je modul za ocjenjivanje preporuka kojim se ažurira korisnički profil nakon što korisnik ocijeni preporučeni sadržaj.
Abstract (english)
This paper describes the design and development of a recommender system that generates the user's profile based on data extracted from social networks. These data include information about the user's preferences and are used to overcome a common problem of recommender systems called "cold start". Based on the generated user's profile, system is capable of finding relevant content for the user. While recommender systems are commonly associated with only one domain, this paper proposes a system architecture that supports content recommendation from more than one domain. The recommender system described in this paper is able to recommend three types of items: a movie, a musician/band and a web article. The user can rate recommended items. Ratings are used to refresh the user's profile which leads to better recommendation process in the future.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:746607
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 on2019-03-13 18:38:32