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Training Machine Learning Algorithms with Temporally Variant Personal Data, and Applications Thereof

  • US 20190311299A1
  • Filed: 04/09/2018
  • Published: 10/10/2019
  • Est. Priority Date: 04/09/2018
  • Status: Active Grant
First Claim
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1. A computer-implemented method for training a machine learning algorithm with temporally variant personal data, comprising:

  • (a) at a plurality of times, monitoring a data source to determine whether data relating to a person has updated;

    (b) when data for the person has been updated, storing the updated data in a database such that the database includes a running log specifying how the person'"'"'s data has changed over time, wherein the person'"'"'s data includes values for a plurality of properties relating to the person;

    (c) receiving an indication that a value for the particular property in the person'"'"'s data was verified as accurate or inaccurate at a particular time;

    (d) retrieving, from the database based on the particular time, the person'"'"'s data, including values for the plurality of properties, that were up-to-date at the particular time; and

    (e) training a model using the retrieved data and the indication such that the model can predict whether another person'"'"'s value for the particular property is accurate, whereby having the retrieved data be current to the particular time maintains the retrieved data'"'"'s significance in training the model.

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