Patent · US Active

Prediction of future occurrences of events using adaptively trained artificial-intelligence processes and contextual data

US12387145B2 · kind B2 · utility

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6References
21Claims
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Key dates

Filing dateMar 3, 2021
Grant dateAug 12, 2025
Priority date
Expiry dateMay 26, 2044

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06F40/40
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

The disclosed embodiments include computer-implemented apparatuses and processes that dynamically predict future occurrences of events using adaptively trained artificial-intelligence processes and contextual data. For example, an apparatus may generate an input dataset based on first interaction data and contextual data associated with a prior temporal interval, and may apply an adaptively trained, gradient-boosted, decision-tree process to the input dataset. Based on the application of the adaptively trained, gradient-boosted, decision-tree process to the input dataset, the apparatus may generate output data representative of a predicted likelihood of an occurrence of an event during a future temporal interval, which may be separated from the prior temporal interval by a corresponding buffer interval. The apparatus may also transmit a portion of the generated output data to a computing system, and the computing system may be configured to generate or modify second interaction data based on the portion of the output data.

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