Patent · US Active

Document analysis system that uses machine learning to predict subject matter evolution of document content

US10402751B2 · kind B2 · utility

1Cited by
2References
20Claims
0Family size

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Key dates

Filing dateMar 21, 2016
Grant dateSep 3, 2019
Priority date
Expiry dateJul 5, 2038

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06N20/00
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

A method includes performing, by a processor: receiving a document containing subject matter related to a course of action, the document comprising a plurality of sub-documents that are related to one another in a time sequence, converting the document to a vector format to generate a vectorized document that encodes a probability distribution of words in the document and transition probabilities between words, applying a machine learning algorithm to the vectorized document to generate an estimated vectorized document, associating the estimated vectorized document with a reference document; predicting future subject matter contained in a future sub-document of the document based on the reference document, and adjusting the course of action responsive to predicting the future subject matter.

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