Patents by Inventor Bradley Ross Cerenzia

Bradley Ross Cerenzia 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: 20180082350
    Abstract: Techniques are described for dynamically generating recommendations for users, such as for products and other items. In at least some situations, the techniques include using multiple recommendation strategies, such as by aggregating recommendation results from multiple different recommendation strategies. Such recommendation strategies may have various forms, and may be based at least in part on data regarding prior interactions of numerous users with numerous items. In addition, information about current selections of a particular user may be gathered based at least in part on providing a GUI (“graphical user interface”) for display to the user that includes selectable information about numerous recommended items, and dynamically updating the displayed GUI with newly generated recommendations of items as the user makes selections of particular displayed recommended items (e.g.
    Type: Application
    Filed: November 29, 2017
    Publication date: March 22, 2018
    Inventors: David Lee Selinger, Michael James DeCourcey, Randall Stuart Fish, Bradley Ross Cerenzia, Tyler David Kohn, Darren Erik Vengroff
  • Publication number: 20150379612
    Abstract: Techniques are described for dynamically generating recommendations for users, such as for products and other items. In at least some situations, the techniques include using multiple recommendation strategies, such as by aggregating recommendation results from multiple different recommendation strategies. Such recommendation strategies may have various forms, and may be based at least in part on data regarding prior interactions of numerous users with numerous items. In addition, information about current selections of a particular user may be gathered based at least in part on providing a GUI (“graphical user interface”) for display to the user that includes selectable information about numerous recommended items, and dynamically updating the displayed GUI with newly generated recommendations of items as the user makes selections of particular displayed recommended items (e.g.
    Type: Application
    Filed: September 3, 2015
    Publication date: December 31, 2015
    Inventors: David Lee Selinger, Michael James DeCourcey, Randall Stuart Fish, Bradley Ross Cerenzia, Tyler David Kohn, Darren Erik Vengroff
  • Publication number: 20120310771
    Abstract: Techniques are described for dynamically generating recommendations for users, such as for products and other items. In at least some situations, the techniques include using multiple recommendation strategies, such as by aggregating recommendation results from multiple different recommendation strategies. Such recommendation strategies may have various forms, and may be based at least in part on data regarding prior interactions of numerous users with numerous items. In addition, information about current selections of a particular user may be gathered based at least in part on providing a GUI (“graphical user interface”) for display to the user that includes selectable information about numerous recommended items, and dynamically updating the displayed GUI with newly generated recommendations of items as the user makes selections of particular displayed recommended items (e.g.
    Type: Application
    Filed: August 13, 2012
    Publication date: December 6, 2012
    Applicant: RICHRELEVANCE, INC.
    Inventors: David Lee Selinger, Michael James DeCourcey, Randall Stuart Fish, Bradley Ross Cerenzia, Tyler David Kohn, Darren Erik Vengroff
  • Patent number: 8244564
    Abstract: Techniques are described for dynamically generating recommendations for users, such as for products and other items. In at least some situations, the techniques include using multiple recommendation strategies, such as by aggregating recommendation results from multiple different recommendation strategies. Such recommendation strategies may have various forms, and may be based at least in part on data regarding prior interactions of numerous users with numerous items. In addition, information about current selections of a particular user may be gathered based at least in part on providing a GUI (“graphical user interface”) for display to the user that includes selectable information about numerous recommended items, and dynamically updating the displayed GUI with newly generated recommendations of items as the user makes selections of particular displayed recommended items (e.g.
    Type: Grant
    Filed: March 31, 2009
    Date of Patent: August 14, 2012
    Assignee: RichRelevance, Inc.
    Inventors: David Lee Selinger, Michael James DeCourcey, Randall Stuart Fish, Bradley Ross Cerenzia, Tyler David Kohn, Darren Erik Vengroff
  • Publication number: 20100250336
    Abstract: Techniques are described for dynamically generating recommendations for users, such as for products and other items. In at least some situations, the techniques include using multiple recommendation strategies, such as by aggregating recommendation results from multiple different recommendation strategies. Such recommendation strategies may have various forms, and may be based at least in part on data regarding prior interactions of numerous users with numerous items. In addition, information about current selections of a particular user may be gathered based at least in part on providing a GUI (“graphical user interface”) for display to the user that includes selectable information about numerous recommended items, and dynamically updating the displayed GUI with newly generated recommendations of items as the user makes selections of particular displayed recommended items (e.g.
    Type: Application
    Filed: March 31, 2009
    Publication date: September 30, 2010
    Inventors: David Lee Selinger, Michael James DeCourcey, Randall Stuart Fish, Bradley Ross Cerenzia, Tyler David Kohn, Darren Erik Vengroff