Patents by Inventor Sean Glerum

Sean Glerum 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).

  • Patent number: 11966372
    Abstract: A novel technique for matching, merging, and combining a new database record with a master database record is described herein. The technique uses specific fields to compare in a unique exact match and fuzzy match combination to determine if a non-exact matching record pair is indeed a matched pair. Once the match is established, the records are merged or combined to utilize the best information from the two records.
    Type: Grant
    Filed: May 1, 2020
    Date of Patent: April 23, 2024
    Assignee: Bottomline Technologies, Inc.
    Inventors: Richard Gagne, Michelle Cloutier, Brian Amend, Sean Glerum
  • Patent number: 11957603
    Abstract: The present invention provides an expandable fusion device capable of being installed inside an intervertebral disc space to maintain normal disc spacing and restore spinal stability, thereby facilitating an intervertebral fusion. In one embodiment, the fusion device includes a body portion, a first endplate, and a second endplate, the first and second endplates capable of being moved in a direction away from the body portion into an expanded configuration or capable of being moved towards the body portion into an unexpanded configuration. The fusion device is capable of being deployed and installed in both configurations.
    Type: Grant
    Filed: June 5, 2023
    Date of Patent: April 16, 2024
    Assignee: Globus Medical Inc.
    Inventors: John Matthews, Mark Weiman, Hilliary Kopp, Chad Glerum, Sean Suh
  • 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
  • Publication number: 20210365904
    Abstract: Disclosed are a system and a method for communicating with a financial institution over a communication network to manage payments of payee initiated by a sender. The system includes a database for storing a plurality of modules, a central server for monitoring and updating the plurality of modules, a processing unit that processes the plurality of modules. The plurality of modules includes a notification module, a payee module, a dashboard module, a refunds module, a payment process module, and a remittance summary module. The notification module allows the sender to send a payment summary to each payee. The payee module allows the payee to upload the payee's details, to select a mode of payment to receive the payment. The payment process module processes the payment as per the mode selected by the payee in the payee module, further processes the payment via cheque mode if the payee fails to update the mode of payment in a pre-defined duration.
    Type: Application
    Filed: August 4, 2021
    Publication date: November 25, 2021
    Applicant: Bottomline Technologies, Inc.
    Inventors: Andrew Scarborough, Phillip Malone, Sean Glerum, Sandhya S. Pillalamarri, Melissa Mikulski, William Cashman
  • 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
  • Patent number: 11094006
    Abstract: Disclosed is a system and a method for communicating with a financial institution over a communication network to manage payments of payee initiated by a sender. The system includes a database for storing plurality of modules, a central server for monitoring and updating the plurality of modules, a processing unit processes the plurality of modules. The plurality of modules includes a notification module, a payee module and a payment process module. The notification module allows the sender to send a payment summary to each payee. The payee module allows the payee to upload payee's details in the central server, to select a mode of payment to receive the payment, to input banking details of the financial institution. The payment process module processes the payment as per the mode selected by the payee in the payee module, further processes the payment via cheque mode if the payee fails to update the mode of payment in a pre-defined duration.
    Type: Grant
    Filed: March 25, 2020
    Date of Patent: August 17, 2021
    Assignee: Bottomline Technologies, Inc.
    Inventors: Andrew Scarborough, Phillip Malone, Sean Glerum, Sandhya S. Pillalamarri, Melissa Mikulski, William Cashman
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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