Testing Deep Learning Recommender Systems Models on Synthetic GAN-Generated Datasets

Testing Deep Learning Recommender Systems Models on Synthetic GAN-Generated Datasets

The published method Generative Adversarial Networks for Recommender Systems (GANRS) allows generating data sets for collaborative filtering recommendation systems. The GANRS source code is available along with a representative set of generated datasets. We have tested the GANRS method by creating m...

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Bibliographic Details
Main Authors: Jesús Bobadilla, Abraham Gutiérrez
Format: Article
Language:English
Published: Universidad Internacional de La Rioja (UNIR) 2025-06-01
Series:International Journal of Interactive Multimedia and Artificial Intelligence
Subjects:
collaborative filtering
deep learning
generative adversarial network
synthetic datasets
recommendation systems
Online Access:https://www.ijimai.org/journal/bibcite/reference/3382
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