【論文筆記】Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks
中文標題：通過圖形神經網絡進行文本分類 發表會議：ACL 2020 文章鏈接：Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks 源代碼：TextING 1 Introduction 1.1問題陳述 ： 文本分類是自然語言處理（NLP）的基礎。傳統的文本分類方法包括樸素
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相關文章
- 1. Every Document Owns Its Structure: Inductive Text Classification via Graph Neur
- 2. 論文筆記：Recurrent Convolutional Neural Networks for Text Classification
- 3. 論文筆記：AAAI 2019 Graph Convolutional Networks for Text Classification
- 4. Structural Image Classification with Graph Neural Networks
- 5. Graph Convolutional Networks for Text Classification閱讀筆記
- 6. 【論文筆記】Heterogeneous Graph Neural Networks for Extractive Document Summarization
- 7. 論文導讀｜Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing
- 8. Recurrent Convolutional Neural Networks for Text Classification
- 9. Graph Convolutional Networks for Text Classification
- 10. 論文筆記之：Semi-supervised Classification with Graph Convolutional Networks