Papers by Guangneng Hu
Personalized Neural Embeddings for Collaborative Filtering with Text (N19-1)
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| Challenge: | Traditional CF approaches exploit user-item relations only and suffer from data sparsity issues. |
| Approach: | They develop a Personalized Neural Embedding framework to exploit both interactions and words seamlessly. |
| Outcome: | The proposed framework exploits both interactions and words seamlessly and predicts user preferences on items based on these embeddings. |
TrNews: Heterogeneous User-Interest Transfer Learning for News Recommendation (2021.eacl-main)
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| Challenge: | Existing content-based recommendations fail when new users use them or a new article is created. |
| Approach: | They propose a model to transfer knowledge from a source corpus to a target corpus and use it to generate representations for unseen users in the future. |
| Outcome: | The proposed model can be used to generate representations for unseen users in the future. |
PrivNet: Safeguarding Private Attributes in Transfer Learning for Recommendation (2020.findings-emnlp)
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| Challenge: | Existing research focuses on the recommendation performance of the target domain while ignores the privacy leakage of the source domain. |
| Approach: | They propose to learn a privacy-aware neural representation by improving target performance while protecting source privacy. |
| Outcome: | The proposed model can disentangle the knowledge benefitting the transfer from leaking the privacy. |