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master's thesis
Sustavi preporučivanja temeljeni na korisničkim sjednicama
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:600167
Luburić, Matej
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Luburić, M. (2022). Sustavi preporučivanja temeljeni na korisničkim sjednicama (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:600167

Luburić, Matej. "Sustavi preporučivanja temeljeni na korisničkim sjednicama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:600167

Luburić, Matej. "Sustavi preporučivanja temeljeni na korisničkim sjednicama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:600167

Luburić, M. (2022). 'Sustavi preporučivanja temeljeni na korisničkim sjednicama', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 01 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:600167

Luburić M. Sustavi preporučivanja temeljeni na korisničkim sjednicama [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 June 01] Available at: https://urn.nsk.hr/urn:nbn:hr:168:600167

M. Luburić, "Sustavi preporučivanja temeljeni na korisničkim sjednicama", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:600167

Metadata
TitleSustavi preporučivanja temeljeni na korisničkim sjednicama
Title (english)Session-based Recommender Systems
AuthorMatej Luburić
MentorAlan Jović (mentor)
Committee memberAlan Jović (predsjednik povjerenstva)
Committee memberVlado Sruk (član povjerenstva)
Committee memberMarin Golub (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-09-21, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Sustavi preporučivanja temeljeni na korisničkim sjednicama (engl. Session-based recommender systems–SBRS) pružaju preporuke isključivo na temelju interakcija korisnika u trenutnoj sjednici i ne zahtijevaju postojanje korisničkih profila ili njihovih cjelokupnih povijesnih aktivnosti. Cilj takvih sustava je da na temelju niza kliknutih artikala u sjednici preporučuje artikle koji su najizgledniji da će na jednog od njih kliknuti korisnik u sljedećem koraku. U ovom diplomskom radu opisani su i primjenjeni modeli koji daju najbolje rezultate na navedenom problemu u području e-trgovine. Model BERT4Rec, originalno objavljen za sustave preporučivanja koji koriste sve prošle sjednice istog korisnika (engl. session-aware recommendation systems), detaljno je objašnjen i prilagođen navedenom problemu. Svi modeli evaluirani su uobičajenim tehnikama za sustave preporučivanja i međusobno uspoređeni. Na kraju rada navedeni su potencijalni smjerovima razvoja ovog područja.
Abstract (english)
Session-based recommender systems (SBRS) provide recommendations based solely on user interactions in current session and do not require the existence of user profiles or their entire historical activities. Based on a series of clicked items in a session, the goal of such systems is to recommend items that are most likely to be clicked on by the user in the next step. In this master thesis, the models that give the best results for the mentioned problem in the field of e-commerce are described and applied. The BERT4Rec model, originally published for session-aware recommender systems, is explained in detail and adapted to the given problem. All models were evaluated using common techniques for evaluating recommender systems and compared with each other. The potential directions of the development of this area are presented at the end of the thesis.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:600167
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 on2023-01-14 09:19:03