Memory Augmented Graph Neural Networks for Sequential Recommendation翻譯
論文下載地址 摘要 關鍵詞：GNN、記憶網絡、雙線性函數 在許多推薦系統中，用戶-物品交互的時間順序可以反映用戶行爲的時間演化和順序。 用戶將與之交互的項可能取決於過去訪問的項。然而，隨着用戶和項目的大量增加，序列推薦系統仍然面臨着不小的挑戰 :(1)短期用戶興趣建模的難度; :(2)獲取長期用戶興趣的難度; (3)項目共現模式的有效建模。 爲了解決這些挑戰，我們提出了一個內存增強圖神經網絡(MA
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相關文章
- 1. Graph Neural Networks for Social Recommendation
- 2. Sequential Recommendation with User Memory Networks簡介
- 3. Visual Question Answering with Memory-Augmented Networks
- 4. FEW-SHOT LEARNING WITH GRAPH NEURAL NETWORKS翻譯
- 5. Introduction to Graph Neural Network翻譯-第四章Vanilla Graph Neural Networks
- 6. GNN:Session-based Recommendation with Graph Neural Networks簡介
- 7. Learning beyond datasets: Knowledge Graph Augmented Neural Networks for Natural language Processing
- 8. Attention and Augmented Recurrent Neural Networks
- 9. 論文分享 - Reasoning with Memory Augmented Neural Networks for Language Comprehension
- 10. Strategies For Pre-Training Graph Neural Networks