Diversifying Furniture Recommendations: A User-Profile-Enhanced Recommender VAE Approach

We propose a novel recommendation model for diversifying furniture recommendations and aligning them more closely with user preferences. Our model builds upon the Recommender Variational Autoencoder (RecVAE), known for its effectiveness and ability to overcome overfitting by linking user feedback wi...

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Detalles Bibliográficos

Principais autores:	Shin Izawa, Keiko Ono, Panagiotis Adamidis
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2025-03-01
Series:	Applied Sciences
Assuntos:	furniture recommendation collaborative filtering variational autoencoders personalization user profiles
Acceso en liña:	https://www.mdpi.com/2076-3417/15/5/2761
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