Data Extrapolation in Social Sensing for Disaster Response

Abstract

This paper complements the large body of social sensing literature by developing means for augmenting sensing data with inference results that "fill-in" missing pieces. Unlike trend-extrapolation methods, we focus on prediction in disaster scenarios where disruptive trend changes occur. A set of prediction heuristics (and a standard trend extrapolation… (More)
DOI: 10.1109/DCOSS.2014.34

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@article{Gu2014DataEI, title={Data Extrapolation in Social Sensing for Disaster Response}, author={Siyu Gu and Chenji Pan and Hengchang Liu and Shen Li and Shaohan Hu and Lu Su and Shiguang Wang and Dong Wang and Md. Tanvir Al Amin and Ramesh Govindan and Charu C. Aggarwal and Raghu K. Ganti and Mudhakar Srivatsa and Amotz Bar-Noy and Peter Terlecky and Tarek F. Abdelzaher}, journal={2014 IEEE International Conference on Distributed Computing in Sensor Systems}, year={2014}, pages={119-126} }