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).
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Patent number: 11966372Abstract: 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: GrantFiled: May 1, 2020Date of Patent: April 23, 2024Assignee: Bottomline Technologies, Inc.Inventors: Richard Gagne, Michelle Cloutier, Brian Amend, Sean Glerum
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Patent number: 11957603Abstract: 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: GrantFiled: June 5, 2023Date of Patent: April 16, 2024Assignee: Globus Medical Inc.Inventors: John Matthews, Mark Weiman, Hilliary Kopp, Chad Glerum, Sean Suh
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Publication number: 20230139699Abstract: 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: ApplicationFiled: October 29, 2021Publication date: May 4, 2023Applicant: Bottomline Technologies, Inc.Inventors: Sean Glerum, Melissa Kutsch, Brian Amend, Jessica Moran
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Publication number: 20210365904Abstract: 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: ApplicationFiled: August 4, 2021Publication date: November 25, 2021Applicant: Bottomline Technologies, Inc.Inventors: Andrew Scarborough, Phillip Malone, Sean Glerum, Sandhya S. Pillalamarri, Melissa Mikulski, William Cashman
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Patent number: 11163955Abstract: 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: GrantFiled: November 2, 2020Date of Patent: November 2, 2021Assignee: Bottomline Technologies, Inc.Inventors: Brian Amend, Melissa Kutsch, Jessica Moran, Sean Glerum
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Patent number: 11094006Abstract: 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: GrantFiled: March 25, 2020Date of Patent: August 17, 2021Assignee: Bottomline Technologies, Inc.Inventors: Andrew Scarborough, Phillip Malone, Sean Glerum, Sandhya S. Pillalamarri, Melissa Mikulski, William Cashman
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Publication number: 20210049326Abstract: 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: ApplicationFiled: November 2, 2020Publication date: February 18, 2021Applicant: Bottomline Technologies (de) Inc.Inventors: Brian Amend, Melissa Kutsch, Jessica Moran, Sean Glerum
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Patent number: 10824809Abstract: 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: GrantFiled: May 19, 2020Date of Patent: November 3, 2020Assignee: Bottomline Technologies (de), Inc.Inventors: Melissa Kutsch, Jessica Moran, Brian Amend, Sean Glerum
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Publication number: 20200279076Abstract: 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: ApplicationFiled: May 19, 2020Publication date: September 3, 2020Applicant: Bottomline Technologies (de) Inc.Inventors: Melissa Kutsch, Jessica Moran, Brian Amend, Sean Glerum
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Patent number: 10699075Abstract: 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: GrantFiled: January 24, 2019Date of Patent: June 30, 2020Assignee: Bottomline Technologies, IncInventors: Brian Amend, Sean Glerum, Melissa Kutsch, Jessica Moran
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Publication number: 20190155903Abstract: 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: ApplicationFiled: January 24, 2019Publication date: May 23, 2019Applicant: Bottomline Technologies (DE), Inc.Inventors: Brian Amend, Sean Glerum, Melissa Kutsch, Jessica Moran
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Patent number: 10235356Abstract: 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: GrantFiled: June 3, 2016Date of Patent: March 19, 2019Assignee: Bottomline Technologies (de), Inc.Inventors: Brian Amend, Sean Glerum, Melissa Kutsch, Jessica Moran
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Publication number: 20170351659Abstract: 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: ApplicationFiled: June 3, 2016Publication date: December 7, 2017Inventors: Brian Amend, Sean Glerum, Melissa Kutsch, Jessica Moran