Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks（閱讀理解）
本文重點： 和一般形式的文本處理方式一樣，並沒有特別大的差異，文章的重點在於提出了一個相似度矩陣 計算過程介紹： query和document中的首先通過word embedding處理後獲得對應的表示矩陣 利用CNN網絡進行處理獲得各自的feature map，接着pooling後獲得query對應的向量表示Xq和document的向量Xd 不同於傳統的Siamense網絡在這一步利用歐式距離或
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相關文章
- 1. Deep Neural Network for Learning to Rank Query-Text Pairs閱讀筆記
- 2. ImageNet Classification with Deep Convolutional Neural Networks -- 解讀
- 3. Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts
- 4. 讀文獻——《ImageNet classification with deep convolutional neural networks》
- 5. ImageNet Classification with Deep Convolutional Neural Networks
- 6. Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks閱讀筆記
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