Patent · US Active

Recommending content using neural networks

US11562209B1 · kind B1 · utility

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18Claims
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Key dates

Filing dateOct 7, 2019
Grant dateJan 24, 2023
Priority date
Expiry dateJul 2, 2041

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06N3/045
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for content recommendation using neural networks. In One aspect, a method includes: receiving context information for an action recommendation from multiple possible actions; processing the context information using a neural network that includes Bayesian neural network layers to generate, for each of the actions, one or more parameters of a distribution over possible action scores for the action, where each parameter for each Bayesian layer is associated with data representing a probability distribution over multiple possible current values for the parameter; for each parameter of each Bayesian neural network layer, selecting the current value for the parameter using data representing probability distribution over possible current values for the parameter; and selecting an action from multiple possible actions using the parameters of the distributions over the possible action scores for the action.

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