Patents by Inventor Leiling Tao

Leiling Tao 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).

  • Detecting anomalies in visualizations
    Patent number: 12353442
    Abstract: Embodiments are directed to managing visualizations of data. Visualizations to monitor may be determined based on metrics associated with the monitored visualizations. Mark values may be sampled from each monitored visualization such that the sampled mark values may be stored with a timestamp. If an amount of the sampled mark values for a monitored visualization exceeds a threshold value mark models may be trained to classify a portion of the sampled mark values associated with the monitored visualization such that the mark models may predict ranges of values for the classified mark values associated with the monitored visualization. If the portion of the classified mark values associated with the monitored visualization has a value outside of the predicted range values, indicating that the monitored visualization may be associated with an anomalous mark value.
    Type: Grant
    Filed: January 28, 2022
    Date of Patent: July 8, 2025
    Assignee: Tableau Software, LLC
    Inventors: Andrew C. Beers, Eric Roy Brochu, Rachel Stern Kalmar, Hon To Ming, David John Mosimann, Leiling Tao, Lu Yu
  • DETECTING ANOMALIES IN VISUALIZATIONS
    Publication number: 20230143734
    Abstract: Embodiments are directed to managing visualizations of data. Visualizations to monitor may be determined based on metrics associated with the monitored visualizations. Mark values may be sampled from each monitored visualization such that the sampled mark values may be stored with a timestamp. If an amount of the sampled mark values for a monitored visualization exceeds a threshold value mark models may be trained to classify a portion of the sampled mark values associated with the monitored visualization such that the mark models may predict ranges of values for the classified mark values associated with the monitored visualization. If the portion of the classified mark values associated with the monitored visualization has a value outside of the predicted range values, indicating that the monitored visualization may be associated with an anomalous mark value.
    Type: Application
    Filed: January 28, 2022
    Publication date: May 11, 2023
    Inventors: Andrew C. Beers, Eric Roy Brochu, Rachel Stern Kalmar, Hon To Ming, David John Mosimann, Leiling Tao, Lu Yu