The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 05, 2025

Filed:

Mar. 31, 2022
Applicant:

Capital One Services, Llc, McLean, VA (US);

Inventors:

Paul Cho, Boston, MA (US);

Gary B. Williams, Williamsburg, VA (US);

Alexander Bussan, Arlington, VA (US);

Eric Campbell, McLean, VA (US);

Piper Alexandra Coble, Richmond, VA (US);

Ralph Lozano, Brooklyn, NY (US);

Mukund Manikantan, McLean, VA (US);

Talyne Derderian Walsh, Rockville, MD (US);

Talha Koc, Jersey City, NJ (US);

Prarthana Bhattarai, Quincy, MA (US);

Assignee:

Capital One Services, LLC, McLean, VA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/3332 (2025.01); G06F 16/332 (2025.01); G06F 16/338 (2019.01);
U.S. Cl.
CPC ...
G06F 16/3338 (2019.01); G06F 16/3326 (2019.01); G06F 16/338 (2019.01);
Abstract

Exemplary embodiments provide methods, mediums, and systems for performing a reusable, intelligent semantic search across a potentially large number of records. Embodiments may be particularly useful for responding to requests for information from regulatory agencies. In one embodiment, an embedding model is trained to embed queries in an embedding space. When a new query is received, the new query is embedded with the embedding model. A set of documents (e.g., previous responses to regulatory inquiries) may be searched using the embedded query and an indexing model that allows for efficient searches of embedding spaces. A number of results may be returned from the document store, and the results may be ranked by a ranking model. User feedback about the quality of the results may be received, and the ranking model may be retrained based on the feedback.


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