Patents by Inventor Neil LAING

Neil LAING 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).

  • Publication number: 20220253875
    Abstract: A system and method generation of adjustable automated forecasts for a promotion. The method includes: determining, using a machine learning model, a set of forecasts each based on different parameters; determining at least one set of optimized parameters that maximize an outcome measure of the forecast for the promotion; generating a graphical representation of the forecast; receiving an adjustment to at least one parameter from a user; determining an adjusted outcome measure of the forecast for the promotion by applying the adjustment to the machine learning model; generating an adjusted graphical representation of the forecast; and displaying the adjusted graphical representation to the user.
    Type: Application
    Filed: April 29, 2022
    Publication date: August 11, 2022
    Inventors: Neil LAING, Waleed AYOUB, Iqbal HABIB, Martin MARK
  • Publication number: 20200380541
    Abstract: A system and method generation of adjustable automated forecasts for a promotion. The method includes: determining, using a machine learning model, a set of forecasts each based on different parameters; determining at least one set of optimized parameters that maximize an outcome measure of the forecast for the promotion; generating a graphical representation of the forecast; receiving an adjustment to at least one parameter from a user; determining an adjusted outcome measure of the forecast for the promotion by applying the adjustment to the machine learning model; generating an adjusted graphical representation of the forecast; and displaying the adjusted graphical representation to the user.
    Type: Application
    Filed: March 21, 2018
    Publication date: December 3, 2020
    Inventors: Neil LAING, Waleed AYOUB, Iqbal HABIB, Martin MARK
  • Publication number: 20170132553
    Abstract: Systems and methods are presented for the computational analysis of the potential relevance of digital data items to key performance indicators. A server system imports bulk amounts of digital data from one or more disparate network-accessible digital data sources. The server system comprises an insight module configured to implement a tree-structure analysis method to identify those events in the digital data most likely to impact selected performance indicators for a given business. The results of the tree-structure analysis method are presented to the business via a user interface displayed on a computing device operated by the business. The most relevant events are presented in a distinctive manner. A recommendation module may be provided to generate recommendations from the insights.
    Type: Application
    Filed: October 17, 2016
    Publication date: May 11, 2017
    Inventors: Dan THEIRL, Kerry LIU, Brian KENG, Waleed AYOUB, Neil LAING