Hookit, LLC

Garrison Hess

Robert J Kraus

Michael Robinson

Scott Tilton

Esther Walker

Adam Smith

A promotion value model uses deep neural networks to learn to calculate the promotion value of a commercial brand. The model determines and reports the promotion value of a plurality of electronic media files each containing at least one commercial brand indicator. The learned model identifies the electronic media files and determines at least one context for each of the at least one commercial brand indicators. Promotion value is modeled with a deep neural network that maps the context for each of the commercial brand indicators to feature vectors mapped to an input layer of the neural network. Network parameters are learned to indicate relative weighted values between transitions of the layers of the neural network.

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Solana Beach, CA, United States of America

Garrison Hess