Automatic Grammatical Evolution-Based Optimization of Matrix Factorization Algorithm
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...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-04-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/10/7/1139 |
| _version_ | 1797438454114549760 |
|---|---|
| author | Matevž Kunaver Árpád Bűrmen Iztok Fajfar |
| author_facet | Matevž Kunaver Árpád Bűrmen Iztok Fajfar |
| author_sort | Matevž Kunaver |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T11:38:07Z |
| format | Article |
| id | doaj.art-6e4a3b431d48416d891517a07b321790 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T11:38:07Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-6e4a3b431d48416d891517a07b3217902023-11-30T23:37:43ZengMDPI AGMathematics2227-73902022-04-01107113910.3390/math10071139Automatic Grammatical Evolution-Based Optimization of Matrix Factorization AlgorithmMatevž Kunaver0Árpád Bűrmen1Iztok Fajfar2Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, SloveniaFaculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, SloveniaFaculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, SloveniaNowadays, 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.https://www.mdpi.com/2227-7390/10/7/1139matrix factorizationgenetic programminggrammatical evolutionrecommender systemsmeta-optimization |
| spellingShingle | Matevž Kunaver Árpád Bűrmen Iztok Fajfar Automatic Grammatical Evolution-Based Optimization of Matrix Factorization Algorithm Mathematics matrix factorization genetic programming grammatical evolution recommender systems meta-optimization |
| title | Automatic Grammatical Evolution-Based Optimization of Matrix Factorization Algorithm |
| title_full | Automatic Grammatical Evolution-Based Optimization of Matrix Factorization Algorithm |
| title_fullStr | Automatic Grammatical Evolution-Based Optimization of Matrix Factorization Algorithm |
| title_full_unstemmed | Automatic Grammatical Evolution-Based Optimization of Matrix Factorization Algorithm |
| title_short | Automatic Grammatical Evolution-Based Optimization of Matrix Factorization Algorithm |
| title_sort | automatic grammatical evolution based optimization of matrix factorization algorithm |
| topic | matrix factorization genetic programming grammatical evolution recommender systems meta-optimization |
| url | https://www.mdpi.com/2227-7390/10/7/1139 |
| work_keys_str_mv | AT matevzkunaver automaticgrammaticalevolutionbasedoptimizationofmatrixfactorizationalgorithm AT arpadburmen automaticgrammaticalevolutionbasedoptimizationofmatrixfactorizationalgorithm AT iztokfajfar automaticgrammaticalevolutionbasedoptimizationofmatrixfactorizationalgorithm |