View source for 17946926. COMPUTER-BASED SYSTEMS CONFIGURED FOR AUTOMATICALLY UPDATING A DATABASE BASED ON AN INITIATION OF A DYNAMIC MACHINE-LEARNING VERIFICATION AND METHODS OF USE THEREOF simplified abstract (Capital One Services, LLC)

=COMPUTER-BASED SYSTEMS CONFIGURED FOR AUTOMATICALLY UPDATING A DATABASE BASED ON AN INITIATION OF A DYNAMIC MACHINE-LEARNING VERIFICATION AND METHODS OF USE THEREOF=


==Organization Name==

[[:Category:Capital One Services, LLC|Capital One Services, LLC]]


[[Category:Capital One Services, LLC]]

==Inventor(s)==

[[:Category:Shabnam Kousha of Washington DC (US)|Shabnam Kousha of Washington DC (US)]][[Category:Shabnam Kousha of Washington DC (US)]]

[[:Category:Joshua Edwards of Philadelphia PA (US)|Joshua Edwards of Philadelphia PA (US)]][[Category:Joshua Edwards of Philadelphia PA (US)]]

[[:Category:Lin Ni Lisa Cheng of Great Neck NY (US)|Lin Ni Lisa Cheng of Great Neck NY (US)]][[Category:Lin Ni Lisa Cheng of Great Neck NY (US)]]

[[:Category:Tyler Maiman of Melville NY (US)|Tyler Maiman of Melville NY (US)]][[Category:Tyler Maiman of Melville NY (US)]]

[[:Category:Asher Smith-rose of Midlothian VA (US)|Asher Smith-rose of Midlothian VA (US)]][[Category:Asher Smith-rose of Midlothian VA (US)]]

==COMPUTER-BASED SYSTEMS CONFIGURED FOR AUTOMATICALLY UPDATING A DATABASE BASED ON AN INITIATION OF A DYNAMIC MACHINE-LEARNING VERIFICATION AND METHODS OF USE THEREOF - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17946926 titled 'COMPUTER-BASED SYSTEMS CONFIGURED FOR AUTOMATICALLY UPDATING A DATABASE BASED ON AN INITIATION OF A DYNAMIC MACHINE-LEARNING VERIFICATION AND METHODS OF USE THEREOF

==Simplified Explanation==

The present disclosure describes a method that involves receiving input data from an external data aggregator, utilizing a machine learning algorithm to generate a database of known queries, updating the database with subsequent input data, performing cross-reference analysis to determine the presence of a data record, predicting triggers associated with the data record, and initiating verification of the data record.

* Receiving input data from external data aggregator
* Utilizing machine learning algorithm to generate a database of known queries
* Updating the database with subsequent input data
* Performing cross-reference analysis to determine presence of data record
* Predicting triggers associated with data record
* Initiating verification of data record

== Potential Applications ==
This technology could be applied in the fields of data security, fraud detection, and personalized user experiences.

== Problems Solved ==
This technology helps in efficiently managing and verifying large amounts of data, improving data accuracy, and enhancing user security.

== Benefits ==
The benefits of this technology include increased data accuracy, improved fraud detection capabilities, and enhanced user trust and security.

== Potential Commercial Applications ==
A potential commercial application of this technology could be in the development of secure data verification systems for financial institutions.

== Possible Prior Art ==
One possible prior art could be the use of machine learning algorithms for data analysis and verification in various industries.

== Unanswered Questions ==
1. How does the machine learning algorithm handle new, unknown queries?
2. What are the potential limitations of this technology in terms of scalability and accuracy?


==Original Abstract Submitted==

In some embodiments, the present disclosure provides an exemplary method that may include steps of receiving input data from at least one external data aggregator; utilizing a trained machine learning algorithm to generate a database of known queries; receiving subsequent input data from the at least one external aggregator; automatically updating the database of known queries associated with the plurality of users; utilizing the trained machine learning algorithm to perform a cross-reference analysis to determine a presence of a data record within the database of known queries; dynamically removing the data record from the database of known queries; utilizing the trained machine learning algorithm to predict a trigger associated with the presence of the at least one data record; and instructing a computing device to initiate a verification of the presence of the at least one data record.



[[Category:G06F16/23]]
[[Category:G06F16/2455]]