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Thursday, March 16 • 4:00pm - 5:30pm
Poster: Mitigating Disasters with Deep Learning from Twitter?

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By including credible data extracted from the Twitter social networking service, the study of earthquakes and tsunamis is being transformed into a Big Data Analytics problem. The challenge of establishing geophysically credible tweets is considered through a combination of Deep Learning and semantics (i.e., knowledge representation). Although there remains cause for optimism in augmenting traditional scientific data with that derived from social networking, ongoing research (e.g., http://credit.pvamu.edu/MCBDA2016/Slides/Day2_Lumb_MCBDA1_Twitter_Tsunami.pdf) is aimed at providing utility in practice. The motivation for success remains strong, as establishing a causal relationship between earthquakes and tsunamis remains problematical, and this in turn complicates any ability to deliver timely, accurate messaging that could prove life-critical. Finally, the applicability of this approach to other disaster scenarios (e.g., oil spills) is considered.

avatar for Ian Lumb

Ian Lumb

Solutions Architect, Univa Corporation
As an HPC specialist, Ian Lumb has spent about two decades at the global intersection of IT and science. Ian received his B.Sc. from Montreal's McGill University, and then an M.Sc. from York University in Toronto. Although his undergraduate and graduate studies emphasized geophys... Read More →

Thursday March 16, 2017 4:00pm - 5:30pm
Exhibit Hall BRC

Attendees (3)