Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks

@inproceedings{Lee2016SequentialSC,
  title={Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks},
  author={Ji Young Lee and Franck Dernoncourt},
  booktitle={HLT-NAACL},
  year={2016}
}
  • Ji Young Lee, Franck Dernoncourt
  • Published in HLT-NAACL 2016
  • Computer Science, Mathematics
  • Recent approaches based on artificial neural networks (ANNs) have shown promising results for short-text classification. [...] Key Result Our model achieves state-of-the-art results on three different datasets for dialog act prediction.Expand Abstract

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 30 REFERENCES

    Automatic dialog act segmentation and classification in multiparty meetings

    VIEW 3 EXCERPTS
    HIGHLY INFLUENTIAL

    Banchs , Jason Williams , and Matthew Henderson

    • Jason Williams Rafael E. Banchs
    • Dialog State Tracking Challenge 4 : Handbook
    • 2015