Sponsorhouse, Inc.

Hookit, LLC

Scott Tilton

Michael Robinson

Robert A Kraus

David C Lin

Robert J Kraus

Esther Walker

Adam Smith

Garrison Hess

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.

Deep neural networks modeling

A method for processing data relationships on electronic media sites includes: receiving a first data string and a second data string corresponding to a first account and at least one submission on the electronic media site; determining a content identifier of the at least one submission; correlating the determined content identifier with a database of identified content; determining a value of the at least one indicator to the data relationship between first and second accounts based on: content, context, frequency, recency, and volume of the indicator; receiving a third data string corresponding to the second account; processing the first and third data strings to determine identities of the first and second accounts; assigning a relationship designation between the first and second accounts; and receiving a fourth data string selected from a plurality of data strings according to a priority determined by a plurality of relationship designations.

Data prioritization through relationship analysis mapping

A system for analyzing and quantifying an impact of an entity's presence within a virtual networking environment to provide an impact scorecard of the entity to a 3party is provided. A server has an API data feed to at least one virtual networking platform. A plurality of factors are extracted from the feed with a plurality of calculators, including a commitment score calculator, a performance score calculator, and a reach score calculator. At least one display dashboard is accessible on the server from a computing device of the 3party. The at least one display dashboard visually displays a marketability assessment of the entity on the virtual networking platform based on the factors from the data feed.

Computerized system for detecting the exposure and impact of an entity within virtual networking platforms

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Cardiff, CA, United States of America

Scott Tilton