Automatic grammatical evolution-based optimization of matrix factorization algorithm

Kunaver, Matevž (avtor), Bürmen, Arpad (avtor), Fajfar, Iztok (avtor)

Nowadays, recommender systems are vital in lessening the information overload by filtering out unnecessary information, thus increasing comfort and quality of life. Matrix factorization (MF) is a well-known recommender system algorithm that offers good results but requires a certain level of system knowledge and some effort on part of the user before use. In this article, we proposed an improvement using grammatical evolution (GE) to automatically initialize and optimize the algorithm and some of its settings. This enables the algorithm to produce optimal results without requiring any prior or in-depth knowledge, thus making it possible for an average user to use the system without going through a lengthy initialization phase. We tested the approach on several well-known datasets. We found our results to be comparable to those of others while requiring a lot less set-up. Finally, we also found out that our approach can detect the occurrence of over-saturation in large datasets.

• Jezik: Angleški jezik
• Ključne besede: matrix factorization, genetic programming, grammatical evolution, recommender systems, meta-optimization
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FE - Fakulteta za elektrotehniko
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2022
• Št. strani: 22 str.
• Številčenje: Vol. 10, iss. 7, art. 1139
• PID: 20.500.12556/RUL-136721
• UDK: 004
• ISSN pri članku: 2227-7390
• DOI: 10.3390/math10071139
• COBISS.SI-ID: 103328771
• Datum objave v RUL: 18.05.2022

Gradivo je del revije

• Naslov: Mathematics
• Skrajšan naslov: Mathematics
• Založnik: MDPI AG
• ISSN: 2227-7390
• COBISS.SI-ID: 523267865

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
• Začetek licenciranja: 01.04.2022

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: matrična faktorizacija, genetsko programiranje, slovnična evolucija, priporočilni sistemi, metaoptimizacija

Projekti

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: P2-0246
• Naslov: ICT4QoL - Informacijsko komunikacijske tehnologije za kakovostno življenje