Abstractive Text Classification Using Sequence-to-convolution Neural Networks
code: https://github.com/tgisaturday/Seq2CNN 我們的模型Seq2CNN包括兩部分，抽取輸入文本摘要的序列部分，處理摘要的卷積部分，然後進行分類，Seq2CNN可以分類不同長度的文本，不進行預處理，提出GWS方法進行訓練，GWS用在損失函數上。 1 Introduction 信息分類的重要性。 文本分類的應用，垃圾郵件過濾，新聞分類，情感分類。 在計算機視
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相關文章
- 1. Recurrent Convolutional Neural Networks for Text Classification
- 2. XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
- 3. TensorFlow Text Classification using Attention Mechanism
- 4. Neural Networks - Multi-class classification
- 5. Abstractive Text Summarization using Seq2Seq RNNs and Beyond
- 6. Structural Image Classification with Graph Neural Networks
- 7. Text Classification
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- 10. ImageNet Classification with Deep Convolutional Neural Networks