Capital One Services, LLC

Julian Duque

Tania Cruz Morales

Dwipam Katariya

Muhammad Uddin

Kimberly Stockley

Samuel Rapowitz

Purva Shanker

Dennis Liu

Kevin M Lowe

Helen Temesghen-Blount

Luis Catacora

In some implementations, a system may receive interaction data associated with interactions between a user and subsets of a plurality of interaction parties. The system may store the interaction data and the as historical interaction data associated with historical interactions of the user. The system may provide the historical interaction data as input to a machine learning model, which may be trained using supervised learning and the historical interactions of the user or historical interactions of one or more other users with one or more of the plurality of interaction parties. The system may receive an output, based on applying the machine learning model to the historical interaction data, that may indicate one or more recommended interaction parties based at least in part on one or more factors, wherein the one or more recommended parties may be local entities local to a geographic location associated with the user.

Machine learning model for recommending interaction parties

The invention relates to generating cryptographic tokens based on characteristic determination. The system may generate and transmit a request for encrypted records from a blockchain node, receive the encrypted records from the blockchain node, decrypt the encrypted records into payload identifiers, retrieve sets of item identifiers based on the payload identifiers, determine characteristics associated with the sets of items, and generate a new cryptographic token that indicates the characteristics.

Systems and methods for user characteristic determination through cryptographic tokenized data

The invention relates to generating cryptographic tokens based on received records. The system may receive a blockchain operation request comprising a plurality of records, encrypt a plurality of records into an encrypted payload, generate a cryptographic token based on the encrypted payload, and cause the cryptographic token to be committed to a blockchain.

Systems and methods for user control and exclusion of cryptographic tokenized data

Methods and systems are described herein for an authentication mechanism that uses cryptographic tokens and eye-tracking data. In particular, the disclosed mechanism may receive an authentication request that includes an identifier of a cryptographic token and retrieve eye-tracking data and an image associated with the cryptographic token. The eye-tracking data may store various coordinates within the image and may be encoded for use in authentication. The disclosed mechanism may then transmit the image to a computing device (e.g., associated with a user) that is able to perform gaze detection as part of an authentication operation. In response, the disclosed mechanism may receive user gaze data collected during the authentication operation and determine whether the eye-tracking data matches the user gaze data. Based on determining that the eye-tracking data matches the user gaze data, the disclosed mechanism may transmit to the computing device an indication of successful authentication.

Using cryptographic tokens and gaze detection for authentication

Disclosed embodiments can include a system for generating experiences. A system receives user data related to interactions by the user. The system identifies a set of trends for the user based on the interactions. The system receives a locational indicator, the locational indicator providing a first destination. The system searches locational data associated with the first destination to identify one or more experiences for the user. The system compares the set of trends with the locational data. The system calculates a first experience for the user. The system outputs, for display on a user device, the first experience.

Systems and methods for using locational indicators and user interactions to provide user experiences

In some implementations, a voice assistance device may receive an indication of a visualization change associated with the virtual or augmented reality environment. The voice assistance device may determine that a change value, calculated based on the indication of the visualization change, satisfies a relevance threshold. The voice assistance device may apply, based on the indicator of change satisfying the relevance threshold, a description model to determine at least one sentence describing the virtual or augmented reality environment. The voice assistance device may apply a text-to-speech model to the at least one sentence to generate a digital sound signal and may transmit, to an output component, the digital sound signal.

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Arlington, VA, United States of America

Julian Duque