Corpus ID: 11270374

Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling

@article{Zhou2016TextCI,
  title={Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling},
  author={Peng Zhou and Z. Qi and Suncong Zheng and Jiaming Xu and Hongyun Bao and Bo Xu},
  journal={ArXiv},
  year={2016},
  volume={abs/1611.06639}
}
  • Peng Zhou, Z. Qi, +3 authors Bo Xu
  • Published 2016
  • Computer Science
  • ArXiv
  • Recurrent Neural Network (RNN) is one of the most popular architectures used in Natural Language Processsing (NLP) tasks because its recurrent structure is very suitable to process variablelength text. RNN can utilize distributed representations of words by first converting the tokens comprising each text into vectors, which form a matrix. And this matrix includes two dimensions: the time-step dimension and the feature vector dimension. Then most existing models usually utilize one-dimensional… CONTINUE READING
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