Controllable Multi-Interest Framework for Recommendation

時間 2021-01-13

標籤算法機器學習論文研讀简体版

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Controllable Multi-Interest Framework for Recommendation ABSTRACT Recently, neural networks have been widely used in e-commerce recommender systems, owing to the rapid development of deep learning. We

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1. IntentGC:a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation
2. Recommendation system framework
3. Graph Neural Networks for Social Recommendation
4. Collaborative Memory Network for Recommendation Systems
5. Deep Learning Recommendation Model for Personalization and Recommendation Systems
6. 論文閱讀：DRN: A Deep Reinforcement Learning Framework for News Recommendation
7. DRN: A Deep Reinforcement Learning Framework for News Recommendation理解
8. ATRank: An Attention-Based User Behavior Modeling Framework for Recommendation 詳解
9. Hierarchical Generative Modeling for Controllable Speech Synthesis筆記
10. CFSNet: Toward a Controllable Feature Space for Image Restoration ICCV2019

>>更多相關文章<<