Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings

@inproceedings{Johnson2016SupervisedAS,
  title={Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings},
  author={Rie Johnson and Tong Zhang},
  booktitle={ICML},
  year={2016}
}
One-hot CNN (convolutional neural network) has been shown to be effective for text categorization (Johnson & Zhang, 2015a;b). We view it as a special case of a general framework which jointly trains a linear model with a non-linear feature generator consisting of ‘text region embedding + pooling’. Under this framework, we explore a more sophisticated region embedding method using Long Short-Term Memory (LSTM). LSTM can embed text regions of variable (and possibly large) sizes, whereas the… CONTINUE READING
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