Patents by Inventor Jessica Moran

Jessica Moran 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).

  • Identifying Non-Exactly Matching Text with Diagonal Matching
    Publication number: 20230139699
    Abstract: A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a string similarity score determined using a Levenshtein distance algorithm, the n-gram or trigram methods, the Jaro-Winkler algorithm, the Cosine similarity algorithm, the Hamming distance algorithm, the Damerau-Levenshtein distance algorithm, or similar. For each comparison, the string similarity score is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches. The keyboard distance is determined by counting a number of key movements required to move from one key to another using diagonal movements.
    Type: Application
    Filed: October 29, 2021
    Publication date: May 4, 2023
    Applicant: Bottomline Technologies, Inc.
    Inventors: Sean Glerum, Melissa Kutsch, Brian Amend, Jessica Moran
  • Identifying non-exactly matching text
    Patent number: 11163955
    Abstract: A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a string similarity score determined using a Levenshtein distance algorithm, the n-gram or trigram methods, the Jaro-Winkler algorithm, the Cosine similarity algorithm, the Hamming distance algorithm, the Damerau-Levenshtein distance algorithm, or similar. For each comparison, the string similarity score is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches.
    Type: Grant
    Filed: November 2, 2020
    Date of Patent: November 2, 2021
    Assignee: Bottomline Technologies, Inc.
    Inventors: Brian Amend, Melissa Kutsch, Jessica Moran, Sean Glerum
  • Identifying Non-Exactly Matching Text
    Publication number: 20210049326
    Abstract: A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a string similarity score determined using a Levenshtein distance algorithm, the n-gram or trigram methods, the Jaro-Winkler algorithm, the Cosine similarity algorithm, the Hamming distance algorithm, the Damerau-Levenshtein distance algorithm, or similar. For each comparison, the string similarity score is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches.
    Type: Application
    Filed: November 2, 2020
    Publication date: February 18, 2021
    Applicant: Bottomline Technologies (de) Inc.
    Inventors: Brian Amend, Melissa Kutsch, Jessica Moran, Sean Glerum
  • Method for identifying non-exactly matching text
    Patent number: 10824809
    Abstract: A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a Levenshtein distance algorithm. For each comparison, the Levenshtein distance is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches.
    Type: Grant
    Filed: May 19, 2020
    Date of Patent: November 3, 2020
    Assignee: Bottomline Technologies (de), Inc.
    Inventors: Melissa Kutsch, Jessica Moran, Brian Amend, Sean Glerum
  • Method for Identifying Non-exactly Matching Text
    Publication number: 20200279076
    Abstract: A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a Levenshtein distance algorithm. For each comparison, the Levenshtein distance is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches.
    Type: Application
    Filed: May 19, 2020
    Publication date: September 3, 2020
    Applicant: Bottomline Technologies (de) Inc.
    Inventors: Melissa Kutsch, Jessica Moran, Brian Amend, Sean Glerum
  • Apparatus and method for identifying text that does not match exactly using dual authentication
    Patent number: 10699075
    Abstract: A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a Levenshtein distance algorithm. For each comparison, the Levenshtein distance is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches.
    Type: Grant
    Filed: January 24, 2019
    Date of Patent: June 30, 2020
    Assignee: Bottomline Technologies, Inc
    Inventors: Brian Amend, Sean Glerum, Melissa Kutsch, Jessica Moran
  • Apparatus and Method for Identifying Text that does not Match Exactly using Dual Authentication
    Publication number: 20190155903
    Abstract: A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a Levenshtein distance algorithm. For each comparison, the Levenshtein distance is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches.
    Type: Application
    Filed: January 24, 2019
    Publication date: May 23, 2019
    Applicant: Bottomline Technologies (DE), Inc.
    Inventors: Brian Amend, Sean Glerum, Melissa Kutsch, Jessica Moran
  • Dual authentication method for identifying non-exactly matching text
    Patent number: 10235356
    Abstract: A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a Levenshtein distance algorithm. For each comparison, the Levenshtein distance is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches.
    Type: Grant
    Filed: June 3, 2016
    Date of Patent: March 19, 2019
    Assignee: Bottomline Technologies (de), Inc.
    Inventors: Brian Amend, Sean Glerum, Melissa Kutsch, Jessica Moran
  • DUAL AUTHENTICATION METHOD FOR IDENTIFYING NON-EXACTLY MATCHING TEXT
    Publication number: 20170351659
    Abstract: A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a Levenshtein distance algorithm. For each comparison, the Levenshtein distance is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches.
    Type: Application
    Filed: June 3, 2016
    Publication date: December 7, 2017
    Inventors: Brian Amend, Sean Glerum, Melissa Kutsch, Jessica Moran
  • Footbed forepart
    Patent number: D530896
    Type: Grant
    Filed: February 6, 2004
    Date of Patent: October 31, 2006
    Assignee: Nine West Development Corporation
    Inventors: Norman Dean, Jessica Moran, Alberto Del Biondi