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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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Principais autores: Shin Izawa, Keiko Ono, Panagiotis Adamidis
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2025-03-01
Serier:Applied Sciences
Fag:
furniture recommendation
collaborative filtering
variational autoencoders
personalization
user profiles
Online adgang:https://www.mdpi.com/2076-3417/15/5/2761
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