Learning semantic representations using convolutional neural networks for web search

  title={Learning semantic representations using convolutional neural networks for web search},
  author={Yelong Shen and Xiaodong He and Jianfeng Gao and Li Deng and Gr{\'e}goire Mesnil},
This paper presents a series of new latent semantic models based on a convolutional neural network (CNN) to learn low-dimensional semantic vectors for search queries and Web documents. By using the convolution-max pooling operation, local contextual information at the word n-gram level is modeled first. Then, salient local fea-tures in a word sequence are combined to form a global feature vector. Finally, the high-level semantic information of the word sequence is extracted to form a global… CONTINUE READING
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