TRAINING A NEURAL NETWORK BASED ON TEMPORAL CHANGES IN ANSWERS TO FACTOID QUESTIONS

A method trains a neural network to identify an event based on discrepancies in answers to factoid questions at different times. One or more processors identify answers to a series of factoid questions. The processor(s) compare the answers from the series of factoid questions in order to determine d...

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Bibliographic Details
Main Authors BRAKE, KYLE M, FROST, KEITH G, VERNIER, STANLEY J, BOXWELL, STEPHEN A
Format Patent
LanguageEnglish
Published 21.05.2020
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:A method trains a neural network to identify an event based on discrepancies in answers to factoid questions at different times. One or more processors identify answers to a series of factoid questions. The processor(s) compare the answers from the series of factoid questions in order to determine discrepancies in the answers at different times, and then train a neural network to identify an event based on the discrepancies in the answers at the different times.
Bibliography:Application Number: US201816191754