US 12,118,317 B2
Techniques to add smart device information to machine learning for increased context
Alan Salimov, San Bruno, CA (US); Anish Khazane, San Francisco, CA (US); and Omar Florez Choque, Oakland, CA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Jun. 1, 2023, as Appl. No. 18/204,767.
Application 18/204,767 is a continuation of application No. 17/941,581, filed on Sep. 9, 2022, granted, now 11,704,500.
Application 17/941,581 is a continuation of application No. 16/859,190, filed on Apr. 27, 2020, granted, now 11,468,241, issued on Oct. 11, 2022.
Application 16/859,190 is a continuation of application No. 16/388,838, filed on Apr. 18, 2019, granted, now 10,679,012, issued on Jun. 9, 2020.
Prior Publication US 2023/0385553 A1, Nov. 30, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 40/30 (2020.01); G06F 16/28 (2019.01); G06F 40/205 (2020.01); G06N 20/00 (2019.01)
CPC G06F 40/30 (2020.01) [G06F 16/283 (2019.01); G06F 40/205 (2020.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. An apparatus to perform contextualized information exchange, comprising:
a memory storing instructions; and
processing circuitry, coupled to the memory, wherein the processing circuitry is operable to execute the instructions that causes the processing circuitry to perform functions, including functions to:
receive information from a user;
infer an inferred result, based on the information and health information associated with the user via a first chatbot model, the first chatbot model trained based on data, the data comprising multiple different data types captured from a computing device for contextualization of dialog data, stored in a data structure, with a chain of values, in a standardized format for use in training the first chatbot model, including individual probability values indicating a probability of correspondence between each of a plurality of data elements and probability values indicating a probability of a relationship between the data elements having a correspondence, wherein the chain of values is generated with the data elements that have been transformed, wherein each data element is transformed by a transformation that is selected based on the data type associated with the respective data element, wherein the data comprises non-dialog data including the health information captured by a smart device associated with the user; and
generate information to exchange with the user based on the inferred result.