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master's thesis
Programska implementacija sustava za preporučivanje
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:087710
Frandolić, Matija
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Frandolić, M. (2023). Programska implementacija sustava za preporučivanje (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:087710

Frandolić, Matija. "Programska implementacija sustava za preporučivanje." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:087710

Frandolić, Matija. "Programska implementacija sustava za preporučivanje." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:087710

Frandolić, M. (2023). 'Programska implementacija sustava za preporučivanje', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 20 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:087710

Frandolić M. Programska implementacija sustava za preporučivanje [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 May 20] Available at: https://urn.nsk.hr/urn:nbn:hr:168:087710

M. Frandolić, "Programska implementacija sustava za preporučivanje", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:087710

Metadata
TitleProgramska implementacija sustava za preporučivanje
Title (english)Program implementation of a recommender system
AuthorMatija Frandolić
MentorMarko Čupić (mentor)
Committee memberMarko Čupić (predsjednik povjerenstva)
Committee memberJan Šnajder (član povjerenstva)
Committee memberŽeljka Mihajlović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-12, Croatia
Abstract
U okviru ovog rada bavimo se implementacijom i vrednovanjem različitih metoda preporučivanja. Poseban naglasak stavljamo na metode neuronskog suradničkog filtriranja (NCF) i matrične faktorizacije (MF). U programskom okviru PyTorch ostvarujemo tri modela neuronskog suradničkog filtriranja: generaliziranu matričnu faktorizaciju (GMF), višeslojni perceptron (MLP) i neuronsku matričnu faktorizaciju (NeuMF). Dodatno, ostvarujemo model obične matrične faktorizacije i matrične faktorizacije s pomakom. Sve modele treniramo i evaluiramo na javno dostupnom skupu podataka MovieLens 1M. Provodimo različite eksperimente te uspoređujemo performanse modela na metrikama HR@k, NDCG@k i MRR@k. Svoja opažanja uspoređujemo s rezultatima iz literature.
Abstract (english)
In this thesis, we focus on the implementation and evaluation of various recommendation methods. We place special emphasis on the methods of Neural Collaborative Filtering (NCF) and Matrix Factorization (MF). Within the PyTorch framework, we implement three NCF models: Generalized Matrix Factorization (GMF), Multi-Layer Perceptron (MLP), and Neural Matrix Factorization (NeuMF). Additionally, we implement a model of plain matrix factorization and matrix factorization with bias. All models are trained and evaluated on the publicly available MovieLens 1M dataset. We conduct various experiments and compare the model's performances using metrics such as HR@k, NDCG@k, and MRR@k. We compare our observations with the results reported in the literature.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:087710
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
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Created on2023-10-11 08:51:30