Patents by Inventor John E. SCHLERF

John E. SCHLERF 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: 20230297621
    Abstract: A device may receive a merchant query including first merchant data associated with a first merchant. The first merchant data may be provided, as input, to a merchant matching model associated with a merchant data structure, the merchant matching model having been trained to determine a measure of confidence that input merchant data corresponds to an existing merchant in the merchant data structure. The device may receive, as output from the merchant matching model, a measure of confidence that the first merchant data corresponds to a second merchant, the second merchant being associated with second merchant data stored in the merchant data structure. The device may also determine, based on the measure of confidence, that the first merchant corresponds to the second merchant. Based on the determination, the device may obtain the second merchant data from the merchant data structure and perform an action based on the second merchant data.
    Type: Application
    Filed: May 25, 2023
    Publication date: September 21, 2023
    Inventors: Pavel FORT, Ashish BANSAL, Chang W. KIM, John E. SCHLERF, Philip SPIEGEL
  • Patent number: 11675845
    Abstract: A device may receive a merchant query including first merchant data associated with a first merchant. The first merchant data may be provided, as input, to a merchant matching model associated with a merchant data structure, the merchant matching model having been trained to determine a measure of confidence that input merchant data corresponds to an existing merchant in the merchant data structure. The device may receive, as output from the merchant matching model, a measure of confidence that the first merchant data corresponds to a second merchant, the second merchant being associated with second merchant data stored in the merchant data structure. The device may also determine, based on the measure of confidence, that the first merchant corresponds to the second merchant. Based on the determination, the device may obtain the second merchant data from the merchant data structure and perform an action based on the second merchant data.
    Type: Grant
    Filed: May 28, 2019
    Date of Patent: June 13, 2023
    Assignee: Capital One Services, LLC
    Inventors: Pavel Fort, Ashish Bansal, Chang W. Kim, John E. Schlerf, Philip Spiegel
  • Publication number: 20190278811
    Abstract: A device may receive a merchant query including first merchant data associated with a first merchant. The first merchant data may be provided, as input, to a merchant matching model associated with a merchant data structure, the merchant matching model having been trained to determine a measure of confidence that input merchant data corresponds to an existing merchant in the merchant data structure. The device may receive, as output from the merchant matching model, a measure of confidence that the first merchant data corresponds to a second merchant, the second merchant being associated with second merchant data stored in the merchant data structure. The device may also determine, based on the measure of confidence, that the first merchant corresponds to the second merchant. Based on the determination, the device may obtain the second merchant data from the merchant data structure and perform an action based on the second merchant data.
    Type: Application
    Filed: May 28, 2019
    Publication date: September 12, 2019
    Inventors: Pavel FORT, Ashish BANSAL, Chang W. Kim, John E. SCHLERF, Philip SPIEGEL
  • Patent number: 10353956
    Abstract: A device may receive a merchant query including first merchant data associated with a first merchant. The first merchant data may be provided, as input, to a merchant matching model associated with a merchant data structure, the merchant matching model having been trained to determine a measure of confidence that input merchant data corresponds to an existing merchant in the merchant data structure. The device may receive, as output from the merchant matching model, a measure of confidence that the first merchant data corresponds to a second merchant, the second merchant being associated with second merchant data stored in the merchant data structure. The device may also determine, based on the measure of confidence, that the first merchant corresponds to the second merchant. Based on the determination, the device may obtain the second merchant data from the merchant data structure and perform an action based on the second merchant data.
    Type: Grant
    Filed: October 27, 2017
    Date of Patent: July 16, 2019
    Assignee: Capital One Services, LLC
    Inventors: Pavel Fort, Ashish Bansal, Chang W. Kim, John E. Schlerf, Philip Spiegel
  • Publication number: 20190121918
    Abstract: A device may receive a merchant query including first merchant data associated with a first merchant. The first merchant data may be provided, as input, to a merchant matching model associated with a merchant data structure, the merchant matching model having been trained to determine a measure of confidence that input merchant data corresponds to an existing merchant in the merchant data structure. The device may receive, as output from the merchant matching model, a measure of confidence that the first merchant data corresponds to a second merchant, the second merchant being associated with second merchant data stored in the merchant data structure. The device may also determine, based on the measure of confidence, that the first merchant corresponds to the second merchant. Based on the determination, the device may obtain the second merchant data from the merchant data structure and perform an action based on the second merchant data.
    Type: Application
    Filed: October 27, 2017
    Publication date: April 25, 2019
    Inventors: Pavel FORT, Ashish BANSAL, Chang W. KIM, John E. SCHLERF, Philip SPIEGEL