Neural Generation of Diverse Questions using Answer Focus, Contextual and Linguistic Features

@article{Harrison2018NeuralGO,
  title={Neural Generation of Diverse Questions using Answer Focus, Contextual and Linguistic Features},
  author={V. Harrison and M. Walker},
  journal={ArXiv},
  year={2018},
  volume={abs/1809.02637}
}
  • V. Harrison, M. Walker
  • Published 2018
  • Computer Science
  • ArXiv
  • Question Generation is the task of automatically creating questions from textual input. In this work we present a new Attentional Encoder--Decoder Recurrent Neural Network model for automatic question generation. Our model incorporates linguistic features and an additional sentence embedding to capture meaning at both sentence and word levels. The linguistic features are designed to capture information related to named entity recognition, word case, and entity coreference resolution. In… CONTINUE READING
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