Patent · US Active

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

US12045703B2 · kind B2 · utility

0Cited by
6References
29Claims
0Family size

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Key dates

Filing dateJan 5, 2022
Grant dateJul 23, 2024
Priority date
Expiry dateJan 5, 2042

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06N3/08
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

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.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.