公开(公告)号：US11989506B2

公开(公告)日：2024-05-21

申请号：US17874855

申请日：2022-07-27

Applicant: Capital One Services, LLC

Inventor： Cruz Vargas ,  Phoebe Atkins ,  Alexander Lin ,  Joshua Edwards ,  Lin Ni Lisa Cheng ,  Rajko Ilincic ,  Max Miracolo ,  Brian McClanahan

IPC: G06F16/30 ,  G06F16/33 ,  G06F16/338 ,  G06F40/194 ,  G06F40/284

CPC classification number: G06F40/194 ,  G06F16/3347 ,  G06F16/338 ,  G06F40/284

Abstract: 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.

公开(公告)号：US20240153490A1

公开(公告)日：2024-05-09

申请号：US18415572

申请日：2024-01-17

Applicant: Capital One Services, LLC

Inventor： Aysu Ezen Can ,  Feng Qiu ,  Guadalupe Bonilla ,  Meredith Leigh Critzer ,  Michael Mossoba ,  Alexander Lin ,  Tyler Maiman ,  Mia Rodriguez ,  Vahid Khanagha ,  Joshua Edwards

IPC: G10L15/01 ,  G06F16/35 ,  G06N5/022 ,  G10L15/02 ,  G10L15/10 ,  G10L15/187 ,  G10L15/22

CPC classification number: G10L15/01 ,  G06F16/35 ,  G06N5/022 ,  G10L15/02 ,  G10L15/10 ,  G10L15/187 ,  G10L15/22 ,  G10L2015/025

Abstract: A system may include processor(s), and memory in communication with the processor(s) and storing instructions configured to cause the system to correct ASR errors. The system may receive a transcription comprising transcribed word(s) and may determine whether the transcribed word(s) exceed associated predefined confidence level(s). Responsive to determining a transcribed word does not exceed a predefined confidence level, the system may generate a predicted word. The system may calculate a distance between numerical representations of the transcribed word and the predicted word and may determine whether the distance exceeds a predefined threshold. Responsive to determining the distance exceeds the predefined threshold, the system may determine whether at least one red flag word of a list of red flag words corresponds to a context of the transcription, and, responsive to making that determination, may classify the transcription as associated with a first category.

公开(公告)号：US20240037458A1

公开(公告)日：2024-02-01

申请号：US17877390

申请日：2022-07-29

Applicant: Capital One Services, LLC

Inventor： Mia RODRIGUEZ ,  Michael Mossoba ,  Vahid Khanagha ,  Joshua Edwards ,  Tyler Maiman ,  Guadalupe Bonilla ,  Aysu Ezen Can ,  Alexander Lin ,  Meredith L. Critzer ,  Feng Qiu

IPC: G06N20/20 ,  G06K9/62

CPC classification number: G06N20/20 ,  G06K9/6256 ,  G06K9/6262

Abstract: Systems and methods for reducing network traffic associated with a service. In some aspects, the systems and methods provide for using a first machine learning model to process a data stream for a communication with a user and generate a confidence score regarding whether to assign a communication suppression flag to the user account. Based on the confidence score not exceeding a first threshold, a communication suppression flag is not assigned to the user account. Based on the confidence score being between first and second thresholds, at least a portion of the data stream is extracted based on temporal proximity to a time stamp of an intent of the user to not receive further communications. Using a second machine learning model, the extracted portion of the data stream is processed to generate a prediction regarding whether to assign a communication suppression flag to the user account.

公开(公告)号：US20240070526A1

公开(公告)日：2024-02-29

申请号：US17899355

申请日：2022-08-30

Applicant: Capital One Services, LLC

Inventor： Samuel Rapowitz ,  Bryant Yee ,  Zachary Sweeney ,  Steven Black ,  Alexander Lin ,  Jenny Melendez ,  Joshua Peters

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Systems and methods of the present disclosure enable variable and dynamic feedback to electronic activities by receiving event data and utilizing a feedback machine learning model to predict an average feedback attribute and an average feedback variability attribute based on the event data. A feedback data entry is added to a user profile to store the average feedback attribute and the average feedback variability attribute. A new event and a new event attribute are received for the user profile, and a feedback probability distribution for the new event is generated based on the new event attribute, the average feedback attribute, and the average feedback variability attribute. A new event feedback is generated for the new event based on a random selection from the feedback probability distribution and is output to a computing device associated with the user profile.

公开(公告)号：US11775533B2

公开(公告)日：2023-10-03

申请号：US17149487

申请日：2021-01-14

Applicant: Capital One Services, LLC

Inventor： Alexander Lin ,  Cruz Vargas ,  Joshua Edwards ,  Max Miracolo ,  Mia Rodriguez ,  Phoebe Atkins

IPC: G06F17/00 ,  G06F16/2457 ,  G06F16/248 ,  G06N20/00

CPC classification number: G06F16/24575 ,  G06F16/248 ,  G06N20/00

Abstract: 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.

公开(公告)号：US11755656B2

公开(公告)日：2023-09-12

申请号：US17838349

申请日：2022-06-13

Applicant: Capital One Services, LLC

Inventor： Phoebe Atkins ,  Max Miracolo ,  Joshua Edwards ,  Brian McClanahan ,  Alexander Lin ,  Lin Ni Lisa Cheng ,  Cruz Vargas

IPC: G06F16/9032 ,  G06F16/901 ,  G06F16/9038 ,  G06F16/9035 ,  G06N20/00 ,  G06F18/214

CPC classification number: G06F16/90332 ,  G06F16/9017 ,  G06F16/9035 ,  G06F16/9038 ,  G06F18/214 ,  G06N20/00

Abstract: 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.

公开(公告)号：US20230252517A1

公开(公告)日：2023-08-10

申请号：US18162891

申请日：2023-02-01

Applicant: Capital One Services, LLC

Inventor： Jenny Melendez ,  Joshua Peters ,  Zachary Sweeney ,  Samuel Rapowitz ,  Steven Black ,  Bryant Yee ,  Alexander Lin

IPC: G06Q30/0207 ,  G06Q20/38 ,  G06Q20/40

CPC classification number: G06Q30/0236 ,  G06Q20/389 ,  G06Q20/4014

Abstract: Disclosed embodiments may include a method for automatically providing customized financial card incentives where the system can identify if a transaction is eligible for additional bonus rewards by determining if the user is a student using a clustering algorithm with user similarity data to generate a probability. Then, if the probability is above a predetermined threshold, a machine learning model with comprehensive user data classifies the user as a student or non-student. Once the user is determined to be a student, the transaction is verified as being an educational purchase using the transaction data or by having the user provide an image of a receipt. Once the transaction is verified, the transaction or items within the transaction qualify for additional rewards that are applied to the user’s account. Users who are not identified as students may qualify for a standard amount of rewards.

公开(公告)号：US20230085433A1

公开(公告)日：2023-03-16

申请号：US17474080

申请日：2021-09-14

Applicant: Capital One Services, LLC

Inventor： Aysu Ezen Can ,  Feng Qiu ,  Guadalupe Bonilla ,  Meredith Leigh Critzer ,  Michael Mossoba ,  Alexander Lin ,  Tyler Maiman ,  Mia Rodriguez ,  Vahid Khanagha ,  Joshua Edwards

IPC: G10L15/01 ,  G10L15/22 ,  G10L15/10 ,  G10L15/187 ,  G10L15/02 ,  G06N5/02 ,  G06F16/35

Abstract: A system may include processor(s), and memory in communication with the processor(s) and storing instructions configured to cause the system to correct ASR errors. The system may receive a transcription comprising transcribed word(s) and may determine whether the transcribed word(s) exceed associated predefined confidence level(s). Responsive to determining a transcribed word does not exceed a predefined confidence level, the system may generate a predicted word. The system may calculate a distance between numerical representations of the transcribed word and the predicted word and may determine whether the distance exceeds a predefined threshold. Responsive to determining the distance exceeds the predefined threshold, the system may determine whether at least one red flag word of a list of red flag words corresponds to a context of the transcription, and, responsive to making that determination, may classify the transcription as associated with a first category.

公开(公告)号：US20220222260A1

公开(公告)日：2022-07-14

申请号：US17149487

申请日：2021-01-14

Applicant: Capital One Services, LLC

Inventor： Alexander Lin ,  Cruz Vargas ,  Joshua Edwards ,  Max Miracolo ,  Mia Rodriguez ,  Phoebe Atkins

IPC: G06F16/2457 ,  G06N20/00 ,  G06F16/248

Abstract: 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.

公开(公告)号：US20250063118A1

公开(公告)日：2025-02-20

申请号：US18450886

申请日：2023-08-16

Applicant: Capital One Services, LLC

Inventor： Joshua Edwards ,  Alexander Lin ,  Mia Rodriguez ,  Guadalupe Bonilla ,  Aysu Ezen Can ,  Michael Mossoba ,  Feng Qiu ,  Tyler Maiman ,  Meredith L. Critzer

IPC: H04M3/51 ,  G10L15/18 ,  G10L15/22

Abstract: In some embodiments, the present disclosure provides an exemplary method that may include steps of monitoring, a conversation script between a call center agent and a customer; utilizing, a speech-to-text deep machine learning model to transcribe the audio call to text; utilizing, a natural language processing deep machine learning model to map intent mappings of the audio call; utilizing, a similarity measurement model to determine a semantic similarity between predefined intent mappings and the intent mappings of the call audio text; determining, an error based on the semantic similarity in the intent mapping call audio text; determining a training session based on the error.