Predicting Salient Updates for Disaster Summarization

  title={Predicting Salient Updates for Disaster Summarization},
  author={Chris Kedzie and Kathleen McKeown and Fernando Diaz},
During crises such as natural disasters or other human tragedies, information needs of both civilians and responders often require urgent, specialized treatment. Monitoring and summarizing a text stream during such an event remains a difficult problem. We present a system for update summarization which predicts the salience of sentences with respect to an event and then uses these predictions to directly bias a clustering algorithm for sentence selection, increasing the quality of the updates… CONTINUE READING
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