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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Hlavní autoři:	Shin Izawa, Keiko Ono, Panagiotis Adamidis
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2025-03-01
Edice:	Applied Sciences
Témata:	furniture recommendation collaborative filtering variational autoencoders personalization user profiles
On-line přístup:	https://www.mdpi.com/2076-3417/15/5/2761
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