Incident prediction and response using deep learning techniques and multimodal data

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United States of America Patent

PATENT NO 10289949
APP PUB NO 20170091617A1
SERIAL NO

14868999

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Abstract

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In an approach to incident prediction and response, one or more computer processors receive one or more alerts corresponding to an incident. The one or more computer processors aggregate the one or more alerts with additional data corresponding to the incident. The one or more computer processors feed the aggregated data into a prediction model, where training of the prediction model uses associated independent stacked Restricted Boltzmann Machines utilizing one or more supervised methods and one or more unsupervised methods. The one or more computer processors determine, based, at least in part, on one or more calculations by the prediction model, at least one probability of the incident. The one or more computer processors determine whether the at least one probability exceeds a pre-defined threshold. In response to determining the at least one probability exceeds a pre-defined threshold, the one or more computer processors send at least one notification.

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Patent Owner(s)

  • INTERNATIONAL BUSINESS MACHINE CORPORATION

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Baughman, Aaron K Silver Spring, US 411 2175
Eggenberger, Christian Wil, CH 33 300
Martin, Andrea I Munich, DE 2 27
Stoessel, Daniel S Gwatt, CH 2 27
Trim, Craig M Sylmar, US 510 2261

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