Patents by Inventor Zachary A. Pustejovsky

Zachary A. Pustejovsky has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Ad preference embedding model and lookalike generation engine
    Patent number: 11403663
    Abstract: Methods, systems and computer program products for automating the association of messages. Data points associated with at least one client device associated with an identifier are logged into an activity database. Labels corresponding to message records are retrieved. Message-signal values representing behavior associated with at least a subset of the message records are also retrieved. The labels are merged with the message-signal values to generate a signal-label collection. A signal-label model is trained based on the signal-label collection, thereby generating a trained signal-label model. A mapping of the one or more activity data points and the plurality of labels are then generated. The embedding that is generated can then be used to find custom audiences.
    Type: Grant
    Filed: May 16, 2019
    Date of Patent: August 2, 2022
    Assignee: Spotify AB
    Inventors: Zachary A. Pustejovsky, Zachary W. Nichols, Jeremiah M. Cohen, David S. Susi
  • AD PREFERENCE EMBEDDING MODEL AND LOOKALIKE GENERATION ENGINE
    Publication number: 20190355011
    Abstract: Methods, systems and computer program products for automating the association of messages. Data points associated with at least one client device associated with an identifier are logged into an activity database. Labels corresponding to message records are retrieved. Message-signal values representing behavior associated with at least a subset of the message records are also retrieved. The labels are merged with the message-signal values to generate a signal-label collection. A signal-label model is trained based on the signal-label collection, thereby generating a trained signal-label model. A mapping of the one or more activity data points and the plurality of labels are then generated. The embedding that is generated can then be used to find custom audiences.
    Type: Application
    Filed: May 16, 2019
    Publication date: November 21, 2019
    Inventors: Zachary A. Pustejovsky, Zachary W. Nichols, Jeremiah M. Cohen, David S. Susi