Artificial intelligence and/or machine learning models trained to predict user actions based on an embedding of network locations

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United States of America Patent

PATENT NO 11699109
APP PUB NO 20220261674A1
SERIAL NO

17732249

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Abstract

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A computer-implemented method can facilitate delivery of targeted content to user devices in situations in which historic tracking data (e.g., cookie data) is generally unavailable and/or unreliable. A p-dimensional embedding of websites can be generated based on a group of user devices for whom tracking data is available. Conversion event data that indicates indicating whether that audience member performed a conversion action can be received. A machine learning model can be trained using the conversion event data and the positions of websites appearing in the conversion event data within the p-dimensional embedding to predict a likelihood of conversion and/or a type of content to provide given a position in the p-dimensional embedding. When an indication that a user device is accessing a website is received, a position of that website in the p-dimensional embedding can be determined and targeted content can be delivered to the user device.

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Patent Owner(s)

  • DSTILLERY, INC.

International Classification(s)

Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Hills, Evan Bard Brooklyn, US 1 5
Jenness, Christopher Allen Brooklyn, US 4 26
Jung, Mark Alan Lewisville, US 1 5
Kaufman, Jason Jerard White Plains, US 4 26
White, Amelia Grieve Old Greenwich, US 9 47
Williams, Melinda Han Brooklyn, US 12 49

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