US 12,321,375 B2
Techniques and components to find new instances of text documents and identify known response templates
Joerg Rings, Chicago, IL (US); William Thomas Romano, Riverview, FL (US); and Andre Gatorano, Palatine, IL (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Dec. 22, 2023, as Appl. No. 18/394,388.
Application 17/674,444 is a division of application No. 16/706,270, filed on Dec. 6, 2019, granted, now 11,288,300, issued on Mar. 29, 2022.
Application 16/706,270 is a division of application No. 16/536,993, filed on Aug. 9, 2019, granted, now 10,540,381, issued on Jan. 21, 2020.
Application 18/394,388 is a continuation of application No. 17/674,444, filed on Feb. 17, 2022, granted, now 11,853,339.
Prior Publication US 2024/0338399 A1, Oct. 10, 2024
Int. Cl. G06F 16/35 (2025.01); G06F 16/334 (2025.01); G06F 16/353 (2025.01); G06F 16/93 (2019.01); G06F 18/22 (2023.01); G06V 10/762 (2022.01); G06V 30/40 (2022.01); G06V 30/418 (2022.01); G06V 30/10 (2022.01)
CPC G06F 16/353 (2019.01) [G06F 16/334 (2019.01); G06F 16/93 (2019.01); G06F 18/22 (2023.01); G06V 10/762 (2022.01); G06V 30/40 (2022.01); G06V 30/418 (2022.01); G06V 30/10 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
recognizing alphanumeric characters in a received notification document that was received by an enterprise, wherein the alphanumeric characters are recognized using an optical character recognition algorithm;
identifying, by a processor, patterns of alphanumeric characters in the recognized alphanumeric characters;
accessing, by the processor, a corpus of classified notification documents;
iteratively comparing, by the processor, the patterns of alphanumeric character patterns to a group of alphanumeric character patterns in each respective classified notification document in the corpus;
based on a result of each comparison, identifying a classified notification document of the corpus having a cosine similarity rating that exceeds a predetermined similarity threshold as matching the received notification document, wherein the cosine similarity is determined between the received notification document and each respective classified notification document in the corpus;
assigning, by the processor, a common theme of classified notification document to the received notification document; and
identifying a document response template for communication of a response to the received notification document, the document response template selected for a group or cluster, of the corpus, associated with the classified notification document, wherein classified notification documents are included in the group or cluster based on cosine similarity ratings between pairs of the classified notification document based on the patterns of alphanumeric characters.