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Personalized recommendation systems offer rapid information access, especially for online news platforms. Generative Adversarial Network (GAN) models have ...
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Dive into the research topics of 'Hybrid Generative Adversarial Networks for News Recommendation'. Together they form a unique fingerprint. Sort by; Weight ...
To bridge this gap, we propose a hybrid generative adversarial network (HGAN) for which we can enforce data density estimation via an autoregressive model and ...
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2.4 Generative adversarial networks for recommendation. GAN proposed by Goodfellow et al. (2014) has achieved effective results in several application areas ...
Jan 29, 2024 · The proposed novel Hybrid-CFGAN model can enhance existing GAN-based recommendation and increase the performance of preference predictions on ...
The proposed novel Hybrid-CFGAN model can enhance existing GAN-based recommendation and increase the performance of preference predictions on textual content ...
Jun 28, 2024 · Generative Adversarial Networks in recommendation algo- rithms, has ... Cho, ''A hybrid generative model for online user behavior ...
Dec 18, 2023 · In this work [9] proposes a hybrid GAN approach to address the data imbalance problem and improve the performance of recommendation systems. The ...
May 29, 2024 · Recommender systems, generative adversarial networks, artificial intelligence, Personalization, recommendations. ... hybrid GAN approach to.
Feb 6, 2021 · We conduct a systematic review on the recommendation models that leverage GANs to alleviate the problem of data sparsity from two aspects: (1) ...