Comparative analysis of matrix factorization techniques and their application to book recommendations systems

Botsiura, I.

Публікація:
Comparative analysis of matrix factorization techniques and their application to book recommendations systems

dc.contributor.author	Botsiura, I.
dc.date.accessioned	2025-04-28T08:26:25Z
dc.date.available	2025-04-28T08:26:25Z
dc.date.issued	2025
dc.description.abstract	This study presents a comparative analysis of three matrix factorization techniques—SVD, SVD++, and NMF—applied to book recommendation systems. The research investigates how each technique decomposes the user-book interaction matrix to uncover latent factors that influence book preferences. Using a standardized book rating dataset, the study evaluates the performance of these algorІТhms based on key metrics such as RMSE, MSE, MAE, FCP, and computational efficiency. By focusing on the abilІТy of these methods to model user-book relationships, this research provides insights into their practical application for improving book recommendations.
dc.identifier.citation	Botsiura I. Comparative analysis of matrix factorization techniques and their application to book recommendations systems / I. Botsiura // Радіоелектроніка та молодь у XXI столітті : матеріали 29-го Міжнар. молодіж. форуму, 16–19 квітня 2025 р. – Харків : ХНУРЕ, 2025. – Т. 6 – С. 236-238.
dc.identifier.uri	https://openarchive.nure.ua/handle/document/30909
dc.language.iso	en_US
dc.publisher	ХНУРЕ
dc.subject	matrix factorization
dc.subject	recommendation system
dc.subject	analysis technique
dc.title	Comparative analysis of matrix factorization techniques and their application to book recommendations systems
dc.type	Thesis
dspace.entity.type	Publication