View source for 17529047. SYSTEMS AND METHODS FOR DATA AGGREGATION AND PREDICTIVE MODELING simplified abstract (Capital One Services, LLC)

=SYSTEMS AND METHODS FOR DATA AGGREGATION AND PREDICTIVE MODELING=


==Organization Name==

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


[[Category:Capital One Services, LLC]]

==Inventor(s)==

[[:Category:Viraj Chaudhary of Katy TX (US)|Viraj Chaudhary of Katy TX (US)]][[Category:Viraj Chaudhary of Katy TX (US)]]

[[:Category:Isaac Yi of Arlington VA (US)|Isaac Yi of Arlington VA (US)]][[Category:Isaac Yi of Arlington VA (US)]]

[[:Category:Lin Ni Lisa Cheng of New York NY (US)|Lin Ni Lisa Cheng of New York NY (US)]][[Category:Lin Ni Lisa Cheng of New York NY (US)]]

[[:Category:Daniel John Marsch of Sterling VA (US)|Daniel John Marsch of Sterling VA (US)]][[Category:Daniel John Marsch of Sterling VA (US)]]

[[:Category:Allison Fenichel of Brooklyn NY (US)|Allison Fenichel of Brooklyn NY (US)]][[Category:Allison Fenichel of Brooklyn NY (US)]]

[[:Category:Jacob Balgoyen of Spotsylvania VA (US)|Jacob Balgoyen of Spotsylvania VA (US)]][[Category:Jacob Balgoyen of Spotsylvania VA (US)]]

==SYSTEMS AND METHODS FOR DATA AGGREGATION AND PREDICTIVE MODELING - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17529047 titled 'SYSTEMS AND METHODS FOR DATA AGGREGATION AND PREDICTIVE MODELING

==Simplified Explanation==

The patent application describes a system and method for secure prediction, specifically related to predicting user utilization amounts based on location information. Here is a simplified explanation of the abstract:

* The system includes a memory and a processor that retrieves location information associated with a user account.
* The processor calculates the average spend over different route options for a specific period of time using the location information.
* A predictive model is applied to the average spend to determine a predicted utilization amount.
* Users with a utilization amount exceeding the predicted amount are identified.
* Notifications are sent to these users to adjust their utilization amount for a specific period of time.
* The system receives responses from the users regarding the notifications.
* The user utilization amount is adjusted to the second value and then reverted back to the first value.

Potential applications of this technology:

* Transportation services: Predicting and adjusting user utilization amounts in ride-sharing or carpooling services based on location information.
* Retail and e-commerce: Predicting and adjusting user utilization amounts for delivery services based on location information.
* Travel and hospitality: Predicting and adjusting user utilization amounts for hotel or accommodation bookings based on location information.

Problems solved by this technology:

* Inefficient resource allocation: By predicting and adjusting user utilization amounts, resources can be allocated more efficiently, reducing waste and improving overall service quality.
* Cost optimization: Adjusting user utilization amounts can help optimize costs for service providers by ensuring resources are utilized effectively.
* Improved user experience: By adjusting utilization amounts based on predicted needs, users can have a better experience with services tailored to their requirements.

Benefits of this technology:

* Cost savings: Service providers can save costs by optimizing resource allocation and reducing waste.
* Enhanced efficiency: By predicting and adjusting utilization amounts, resources can be utilized more efficiently, leading to improved overall efficiency.
* Personalized service: Users can benefit from services tailored to their specific needs, resulting in a better user experience.


==Original Abstract Submitted==

Systems and methods for secure prediction can include a memory and a processor that is configured to retrieve location information associated with a user account and calculate an average spend over one or more route options for a first period of time based on the location information. The processor can be configured to apply a predictive model to the average spend to determine a predicted utilization amount, identify one or more users that have a user utilization amount exceeding the predicted utilization amount, transmit one or more notifications to adjust the user utilization amount from a first value to a second value for a second period of time, and receive one or more responses that are responsive to the one or more notifications. The processor can be configured to adjust the user utilization amount to the second value and revert the user utilization amount back to the first value.



[[Category:G06N5/02]]