Detecting and Explaining Causes From Text For a Time Series Event

@inproceedings{Kang2017DetectingAE,
  title={Detecting and Explaining Causes From Text For a Time Series Event},
  author={Dongyeop Kang and Varun Gangal and Ang Lu and Zheng Chen and Eduard H. Hovy},
  booktitle={EMNLP},
  year={2017}
}
Explaining underlying causes or effects about events is a challenging but valuable task. We define a novel problem of generating explanations of a time series event by (1) searching cause and effect relationships of the time series with textual data and (2) constructing a connecting chain between them to generate an explanation. To detect causal features from text, we propose a novel method based on the Granger causality of time series between features extracted from text such as N-grams… 

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