Capital One Services, LLC

Cruz Vargas

Phoebe Atkins

Bryant Alan Yee

Lin Ni Lisa Cheng

Joshua S Edwards

Michael Bakr Mossoba

Max Miracolo

Alexander Lin

Brian McClanahan

Rajko Ilincic

Latika Gulati

Viraj Chaudhary

Lukiih Cuan

Lea Cody

Deny Daniel

Tyler Maiman

Jennifer Kwok

Joshua Peters

Matthew Peroni

Jeffrey Rule

Sophie Bermudez

Daniel John Marsch

William Carroll

Andrea Montealegre

Mia Rodriguez

Adam Vukich

Salik Shah

George Bergeron

Eric Loucks

Louis Buell

Sarah Olsen

James Holt Crews, Jr

Systems and methods of the present disclosure enable database search. The systems and/or methods may include receiving a search query that includes an input document having text. Word embeddings are generated within the input document, where the word embeddings include vector representations of words in the text of the input document. An average input document word embedding vector is determined for the word embeddings of the input document. A set of stored documents is accessed, where each stored document includes a stored text has a particular average stored document word embedding vector. A similarity model is used to determine a similarity metric measuring the similarity between the input document and each stored document based on the average input document word embedding vector and the particular average stored document word embedding vector of each stored document.

Systems for database searching and database schemas management and methods of use thereof

Methods and systems disclosed herein describe customizing searching. Search queries may be customized according to a user's preferences. A user may emphasize or indicate that additional weight should be given to one or more terms in a search query. Terms that are weighted higher may have a larger impact on the results that are returned in response to the search query. In addition to changing the terms in a search query, a user may provide a weight for each term. Each term in a search query may be weighted to varying degrees, giving a user more control over the results that are returned. The weights may be used with machine learning techniques to generate a vector representation of a search query. The vector representation of the search query may be compared with vector representations of search objects to determine results that match the search query.

Customizing search queries for informational retrieval

Embodiments are directed to systems and techniques to generate random numbers via contactless cards.

Devices and techniques to perform entropy-based randomness via a contactless card

In some implementations, a storage optimization system may receive a plurality of emails. Accordingly, the system may identify at least one email associated with a limited capacity in the plurality of emails. The system may further scan, from the at least one email, one or more hyperlinks to determine a website associated with the at least one email and an identifier associated with an event. The system may determine, using a database, a traversal path and at least one application programming interface (API) call associated with the website. Accordingly, the system may traverse the website using the traversal path and the at least one API using the identifier to determine that the limited capacity is filled. The system may delete the at least one email associated with the limited capacity based on determining that the limited capacity is filled.

Storage space optimization for emails

Systems and methods of the present disclosure enable improved content filtering by determining a profile state of the user profile based at least in part on at least one attribute of the user profile and determining a user profile criterion associated with the user profile based on the profile state including a threshold value to trigger a filter parameter associated with the profile objective, where the filter parameter comprises a content type to be processed so as to facilitate achieving the profile objective. The filter parameter is determined based on the profile state surpassing the user profile criterion. A content recognition model is used to identify a message content of each message. An electronic message that matches the content type is identified and filtered at the electronic messaging client to prevent the content from being presented.

Computer-based systems programmed for automatic adaptive content-based processing of electronic messages and methods of use thereof

Example embodiments of information-shielding cards and systems and methods of fabricating the same are provided. An information-shielding card can comprising a substrate comprising a first layer, a second layer, a third layer, a chip embedded in the second layer, and a quick-response (QR) code formed on the second layer. The second layer can be disposed between the first layer and the third layer. The first layer can comprise a first material that is transparent when exposed to a non-visible light, the second layer can comprise a second material that is opaque when exposed to visible light and when exposed to non-visible light, and the third layer comprises a third material that is transparent when exposed to a non-visible light.

Information-shielding cards and systems and methods for fabricating the same

Example embodiments of systems, methods, and computer-accessible mediums for identity verification and transaction authentication are provided. An exemplary system can comprise an application, a user device, and a server. The application can prompt a removal of a card chip, prompt an insertion of the card chip into the user device, determine an orientation of the card chip after the insertion of the card chip into the user device, and transmit, to the card chip, a first message. The card chip can encrypt the first message via one or more authentication protocols to generate an encrypted first message, transmit, to the server, the encrypted first message. The server can decrypt the encrypted first message, verify the decrypted first message, and transmit a second message to the application, wherein the application is configured to display a verification notification in response to the second message.

Systems and methods for chip-based identity verification and transaction authentication

In some embodiments, the present disclosure provides an exemplary method that may include steps of receiving an input text data retrieved from a transcription associated with a previously recorded audio data file between a user of a plurality of users and an agent associated with a call center; identifying personal information associated with the user of the plurality of users from the input text data by inputting the input text data into a trained machine learning model; determining at least one key term within the personal information associated with the user of the plurality of users; automatically determining a confidence positivity score associated with the at least one key term; automatically extracting a plurality of tuples from the input text data; storing the plurality of tuples in an external database; and automatically generating a call script for conducting a subsequent call with the user.

Computer-based systems configured for automated extraction of data from inputs and methods of use thereof

In some implementations, a transaction card may include a card body, a magnetic stripe connected to the card body at a magnetic stripe region of the card body, and a tactile element at the magnetic stripe region of the card body.

Transaction card with tactile elements

Disclosed embodiments may include a system that may receive an interaction message associated with an interaction a user has with an application or website, the interaction message may include an error message or a repeated action message. The system may identify, using a first machine learning model, one or more issues associated with the interaction message, retrieve one or more troubleshooting steps mapped to the one or more issues, and generate a first message comprising the one or more troubleshooting steps and a feedback request on an effectiveness of the one or more troubleshooting steps. The system may transmit the first message to the user, receive feedback from the user in response to the feedback request, and determine whether the feedback is negative. When the feedback is negative, the system may transmit a second message to a representative requesting the representative call the user.

System and methods for identifying and troubleshooting customer issues to preempt customer calls

A processor may receive data and generate a quantified representation of the data by processing the data using at least one machine learning (ML) algorithm, the quantified representation of the data indicating a sentiment of content of the data. The processor may automatically revise the content of the communications data. The revising may include determining a reaction to the content of the communications data, generating a quantified representation of the reaction, determining a difference between the quantified representation of the reaction and the quantified representation of the communications data, identifying, based on the difference, a portion of the content having an unintended sentiment, and replacing the portion of the content with different content.

Feedback control for automated messaging adjustments

Systems as described herein may analyze big data to generate predictions for Software-as-a-Service (SaaS) offerings and/or other subscription-based software. A prediction system may receive small business transaction data comprising payment information between a plurality of merchants and a software vendor. The prediction system may receive enterprise merchant insights information. The prediction system may identify, based on the small business transaction data and the enterprise merchant insights information, recurring transactions using a first machine learning model. The prediction system may generate an average contract price and a confidence score, using a second machine learning model. The prediction system may generate a recommendation comprising a renewal rate. Based on a determination that a service provided by the software vendor is coming due for renewal, the prediction system may send, to a particular merchant, an alert associated with the renewal and the recommendation.

Predictions based on analysis of big data

Example embodiments of systems, methods, and computer-accessible mediums for transaction authorization are provided. An exemplary system can comprise a card including an input device and a display device in data communication with a server. The server can generate an authorization passcode upon an initiation of a transaction session, and the card can receive an entered passcode through the input device, display the entered passcode on the display device, and transmit the entered passcode to the server for comparison to the authorization passcode. Upon a determination that the entered passcode is a match for the authorization passcode, the server can transmit a match notification indicating the transaction session is valid, and upon a determination that the entered passcode is a mismatch for the authorization passcode, the server can transmit a mismatch notification terminating the transaction session.

Systems and methods for card authorization

Disclosed herein are systems and methods for providing contextualized reviews. A customer can make a review, such as reviewing a product or a business, outlining their experience. To provide additional emotional context, biometric data can be obtained and compared to the customer's historical biometric data. Upon determining that the biometric data has deviated from the historical biometric data, the review data from the review can be revised to include a notification. The customer can also be alerted and warned to not post the review if their emotional state is found to be negative. The process can be repeated on a plurality of customers opted-in to the contextualized review system. For the plurality of customers, a plurality of reviews can be analyzed for a business or service provider by, for instance, emphasizing emotional reviews, ranking the reviews, or filtering out non-emotional reviews.

Systems and methods for providing contextualized reviews

Methods and systems are disclosed herein for secure communication between computing devices. A mobile device may communicate with an untrusted device to cause the untrusted device to send information (e.g., encrypted information that the untrusted device is unable to decrypt) to a server using an Internet connection of the untrusted device. The mobile device may have limited or no access to the Internet. To prevent potential security risks associated with using a public or untrusted device, the mobile device may encrypt information stored on the mobile device (e.g., stored in a mobile application associated with the server), send it to the untrusted device (e.g., by displaying a QR code to a camera of the untrusted device), and the untrusted device may send the information to the server via a network connection of the untrusted device.

Growing community of inventors

Denver, CO, United States of America

Cruz Vargas