Auto-tuning HyperParameters of SGD Matrix Factorization-Based Recommender Systems Using Genetic Algorithm

Habib Irani, Fatemeh Elahi, Mahmood Fazlali, Mahyar Shahsavari, Bahar Farahani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recommender systems enable companies to generate meaningful recommendations to users for items or products that might interest them. Stochastic Gradient Descent Matrix Factorization (SGD-MF) is one of the most popular model-based recommender systems. Fractional Adaptive Stochastic Gradient Descent matrix factorization (FASGD-MF) is a subset of SGD-MF-based models that apply fractional calculus in an adaptive way. There are some hyperparameters in these models that impact the quality of the recommender system. However, searching the hyperparameter space to find the best configuration using an exhaustive search is often a time-consuming task. This paper employs a genetic algorithm as a search metaheuristic to tackle this problem. The proposed method is designed based on non-uniform mutation and whole arithmetic crossover. The results indicate that optimizing hyperparameters by the proposed method not only adjusts the values of hyperparameters automatically but also can improve the quality of SGD-MF-based models. Implementing the proposed genetic algorithm on two datasets (MovieLens 100K and MovieLens 1M) verifies the assertion about the performance.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)
Place of PublicationBarcelona, Spain
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)9781665483568
DOIs
Publication statusPublished - 3 Aug 2022
Event2022 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2022 - Barcelona, Spain
Duration: 1 Aug 20223 Aug 2022

Publication series

Name2022 IEEE International Conference on Omni-Layer Intelligent Systems, COINS

Conference

Conference2022 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2022
Country/TerritorySpain
CityBarcelona
Period1/08/223/08/22

Keywords

  • Collaborative Filtering
  • Genetic Algorithm
  • Matrix Factorization
  • Optimization
  • Recommender System

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