Programska implementacija sustava za preporučivanje

master's thesis

• Title (english): Program implementation of a recommender system
• Author: Matija Frandolić
• Mentor: Marko Čupić (mentor)
• Committee member: Marko Čupić (predsjednik povjerenstva)
• Committee member: Jan Šnajder (član povjerenstva)
• Committee member: Željka Mihajlović (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2023-07-12, 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: sustav preporučivanja; suradničko filtriranje; neuronsko suradničko filtriranje; matrična faktorizacija; generalizirana matrična faktorizacija; višeslojni perceptron; neuronska matrična faktorizacija
• Keywords (english): recommender system; collaborative filtering; neural collaborative filtering; matrix factorization; generalized matrix factorization; multi-layer perceptron; neural matrix factorization
• Language: croatian
• URN:NBN: urn:nbn:hr:168:087710
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-10-11 08:51:30