Patents by Inventor Mark G. Kane

Mark G. Kane 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).

  • Algorithm for the non-exact matching of large datasets
    Patent number: 11681717
    Abstract: A two-step algorithm for conducting near real-time fuzzy searches of a target on one or more large data sets is described. This algorithm includes the simplification of the data by removing grammatical constructs to bring the target search term (and the stored database) to their base elements and then performing a Levenstein comparison to create a subset of the data set that may be a match. Then performing a scoring algorithm while comparing the target to the subset of the data set to identify any matches.
    Type: Grant
    Filed: October 6, 2022
    Date of Patent: June 20, 2023
    Assignee: Bottomline Technologies, Inc.
    Inventors: Kaiyu Pan, Richard J. Diekema, Jr., Mark G. Kane
  • Algorithm for the Non-exact Matching of Large Datasets
    Publication number: 20230051025
    Abstract: A two-step algorithm for conducting near real-time fuzzy searches of a target on one or more large data sets is described. This algorithm includes the simplification of the data by removing grammatical constructs to bring the target search term (and the stored database) to their base elements and then performing a Levenstein comparison to create a subset of the data set that may be a match. Then performing a scoring algorithm while comparing the target to the subset of the data set to identify any matches.
    Type: Application
    Filed: October 6, 2022
    Publication date: February 16, 2023
    Applicant: Bottomline Technologies, Inc.
    Inventors: Kaiyu Pan, Richard Diekema, JR., Mark G. Kane
  • Non-exact matching of large datasets
    Patent number: 11475027
    Abstract: A two-step algorithm for conducting near real-time fuzzy searches of a target on one or more large data sets is described. This algorithm includes the simplification of the data by removing grammatical constructs to bring the target search term (and the stored database) to their base elements and then perform a Levenstein comparison to create a subset of the data set that may be a match. Then performing a scoring algorithm while comparing the target to the subset of the data set to identify any matches.
    Type: Grant
    Filed: January 20, 2022
    Date of Patent: October 18, 2022
    Assignee: Bottomline Technologies, Inc.
    Inventors: Kaiyu Pan, Richard J. Diekema, Jr., Mark G. Kane
  • Non-exact Matching of Large Datasets
    Publication number: 20220147525
    Abstract: A two-step algorithm for conducting near real-time fuzzy searches of a target on one or more large data sets is described. This algorithm includes the simplification of the data by removing grammatical constructs to bring the target search term (and the stored database) to their base elements and then perform a Levenstein comparison to create a subset of the data set that may be a match. Then performing a scoring algorithm while comparing the target to the subset of the data set to identify any matches.
    Type: Application
    Filed: January 20, 2022
    Publication date: May 12, 2022
    Applicant: Bottomline Technologies, Inc.
    Inventors: Kaiyu Pan, Richard J. Diekema, JR., Mark G. Kane
  • Two step algorithm for non-exact matching of large datasets
    Patent number: 11238053
    Abstract: A two-step algorithm for conducting near real-time fuzzy searches of a target on one or more large data sets is described. This algorithm includes the simplification of the data by removing grammatical constructs to bring the target search term (and the stored database) to their base elements and then perform a Levenstein comparison to create a subset of the data set that may be a match. Then performing a scoring algorithm while comparing the target to the subset of the data set to identify any matches.
    Type: Grant
    Filed: May 20, 2021
    Date of Patent: February 1, 2022
    Assignee: Bottomline Technologies, Inc.
    Inventors: Mark G. Kane, Richard J. Diekema, Jr., Kaiyu Pan
  • Two Step Algorithm for Non-exact Matching of Large Datasets
    Publication number: 20210279238
    Abstract: A two-step algorithm for conducting near real-time fuzzy searches of a target on one or more large data sets is described. This algorithm includes the simplification of the data by removing grammatical constructs to bring the target search term (and the stored database) to their base elements and then perform a Levenstein comparison to create a subset of the data set that may be a match. Then performing a scoring algorithm while comparing the target to the subset of the data set to identify any matches.
    Type: Application
    Filed: May 20, 2021
    Publication date: September 9, 2021
    Applicant: Bottomline Technologies, Inc.
    Inventors: Mark G. Kane, Richard J. Diekema, JR., Kaiyu Pan
  • Two step algorithm for non-exact matching of large datasets
    Patent number: 11042555
    Abstract: A two step algorithm for conducting near real time fuzzy searches of a target on one or more large data sets is described. This algorithm includes the simplification of the data by removing grammatical constructs to bring the target search term (and the stored database) to their base elements and then perform a Levenstein comparison to create a subset of the data set that may be a match. Then performing a scoring algorithm while comparing the target to the subset of the data set to identify any matches.
    Type: Grant
    Filed: June 28, 2019
    Date of Patent: June 22, 2021
    Assignee: Bottomline Technologies, Inc.
    Inventors: Mark G. Kane, Richard J. Diekema, Jr., Kaiyu Pan