ANONYMOUS UNCENSORABLE CRYPTOGRAPHIC CHAINS
Granted: February 1, 2024
Application Number:
20240039741
A method implements anonymous uncensorable cryptographic chains. The method includes receiving, from a first application, verifiable data for a current record and unverified data for the current record. The unverified data for the current record was received by the first application from a second application. The method further includes verifying the verifiable data for the current record with unverified data from a previous record. The method further includes recording the verifiable…
PREDICTING DISCRETE OUTCOMES IN COMPUTER APPLICATIONS USING MACHINE LEARNING MODELS ON TIME SERIES DATA INSTANCES
Granted: February 1, 2024
Application Number:
20240037415
Systems and methods may predict whether a user will abandon an application. Initially, different features are extracted from a time series of numerical values rendered by the application. A machine learning model is trained using a supervised approach on the extracted features to map the known and labeled outputs. In this supervised approach, the output may be binary with a “0”-label for a user that has left the application in the middle of a task and a “1”-label for the user who…
NATURAL LANGUAGE QUERY DISAMBIGUATION
Granted: February 1, 2024
Application Number:
20240037327
A method, computer program product, and system are provided. A first natural language text is received via a user interface. A generative pretrained transformer machine learning model processes the first natural language text and a context to identify a first intent. The processing is based in part on a syntax determined from a set of natural language completion paradigms. The generative transformer machine learning model maps the first set of parameters to a first query. The mapping is…
TEXT FEATURE GUIDED VISUAL BASED DOCUMENT CLASSIFIER
Granted: February 1, 2024
Application Number:
20240037125
A visual-based classification model influenced by text features as a result of the outputs of a text-based classification model is disclosed. A system receives one or more documents to be classified based on one or more visual features and provides the one or more documents to a student classification model, which is a visual-based classification model. The system also classifies, by the student classification model, the one or more documents into one or more document types based on one…
TRANSFORMING DATA VISUALIZATIONS DURING PAGE TRANSITIONS
Granted: February 1, 2024
Application Number:
20240037124
Systems and methods for transforming a data visualization are disclosed. An example method includes presenting the data visualization on a first page of a display of the computing device, the data visualization representing at least a first portion of a data set, receiving a visualization transformation command from a user, in response to receiving the visualization transformation command, navigating to a second page of the display, and, during the navigation, transforming the data…
AUTOMATED DATABASE OWNERSHIP ATTRIBUTION
Granted: February 1, 2024
Application Number:
20240037112
Systems and methods for automated techniques that generate queryable database table ownership attribution information in real-time. In addition to generating ownership attribution information, system and methods provide a novel framework for creating bi-partite graphs and generating insightful graph data.
ANONYMOUS UNCENSORABLE CRYPTOGRAPHIC CHAINS
Granted: February 1, 2024
Application Number:
20240039741
A method implements anonymous uncensorable cryptographic chains. The method includes receiving, from a first application, verifiable data for a current record and unverified data for the current record. The unverified data for the current record was received by the first application from a second application. The method further includes verifying the verifiable data for the current record with unverified data from a previous record. The method further includes recording the verifiable…
PREDICTING DISCRETE OUTCOMES IN COMPUTER APPLICATIONS USING MACHINE LEARNING MODELS ON TIME SERIES DATA INSTANCES
Granted: February 1, 2024
Application Number:
20240037415
Systems and methods may predict whether a user will abandon an application. Initially, different features are extracted from a time series of numerical values rendered by the application. A machine learning model is trained using a supervised approach on the extracted features to map the known and labeled outputs. In this supervised approach, the output may be binary with a “0”-label for a user that has left the application in the middle of a task and a “1”-label for the user who…
INTELLIGENT DOCUMENT PROCESSING
Granted: January 25, 2024
Application Number:
20240029175
Systems and methods that process, classify, and provide intelligent insights related to received documents such as notice documents in real-time. The system and methods leverage a novel framework of artificial intelligence and machine learning techniques to identify a requirement in the document (e.g., a government notice) and generate actionable suggestions thereto.
CROSS-HIERARCHICAL MACHINE LEARNING PREDICTION
Granted: January 25, 2024
Application Number:
20240028973
A method including training, using training data including a first ontological hierarchical level, trained machine learning models (MLMs) to predict a first output type including a second ontological hierarchical level different than the first ontological hierarchical level. The method also includes generating instances of the first output type by executing the trained MLMs on unknown data including the first ontological hierarchical level. Outputs of the trained MLMs include the…
INTELLIGENT DOCUMENT PROCESSING
Granted: January 25, 2024
Application Number:
20240029175
Systems and methods that process, classify, and provide intelligent insights related to received documents such as notice documents in real-time. The system and methods leverage a novel framework of artificial intelligence and machine learning techniques to identify a requirement in the document (e.g., a government notice) and generate actionable suggestions thereto.
CROSS-HIERARCHICAL MACHINE LEARNING PREDICTION
Granted: January 25, 2024
Application Number:
20240028973
A method including training, using training data including a first ontological hierarchical level, trained machine learning models (MLMs) to predict a first output type including a second ontological hierarchical level different than the first ontological hierarchical level. The method also includes generating instances of the first output type by executing the trained MLMs on unknown data including the first ontological hierarchical level. Outputs of the trained MLMs include the…
ADVERSARIAL DETECTION USING DISCRIMINATOR MODEL OF GENERATIVE ADVERSARIAL NETWORK ARCHITECTURE
Granted: January 4, 2024
Application Number:
20240005651
A method includes training, using first real data objects, a generative adversarial network having a generator model and a discriminator model to create a trained generator model that generates realistic data, and training, using adversarial data objects and second real data objects, the discriminator model to output an authenticity binary class for the adversarial data objects and the second real data objects. The method further includes deploying the discriminator model to a production…
ATTRIBUTE SELECTION FOR MATCHMAKING
Granted: December 28, 2023
Application Number:
20230419344
Methods and systems for assisting entities with improving the effectiveness of their profiles are disclosed. An example method is performed by one or more processors of a system and includes storing profile data including profiles identifying attributes associated with respective entities, obtaining a selection data vector including values each indicating a selection rate for a respective entity, generating, using a trained analysis model, selection prediction data predicting, for each…
ASSESSMENT OF USER PRICE SENSITIVITY
Granted: December 28, 2023
Application Number:
20230419341
Systems and methods for assessment of user price sensitivity using a predictive model are disclosed. An example method may be performed by one or more processors of a retention system and include retrieving traversal sequences including lists of pages users accessed prior to price notifications, labeling the traversal sequences based on whether users terminated sessions upon the notifications, transforming the traversal sequences into graphs based on identifiers assigned to the pages and…
DYNAMIC SCHEMA MAPPING BETWEEN MICROSERVICES
Granted: December 28, 2023
Application Number:
20230419139
Disclosed dynamic schema mapping systems and methods monitor network traffic between different microservices and train mapping models based on the monitored network traffic using unsupervised training. This training of the mapping models generates a probability distribution tensor that shows the probabilistic associations of different key-value pairs of the schemas of different microservices. The trained mapping models are used to map a schema from a source microservice to another schema…
MATCHING VALIDATION
Granted: December 21, 2023
Application Number:
20230410212
Matching validation includes obtaining a candidate match between a target entity and a candidate application user and filtering multiple transaction records of multiple application users to obtain a subset of the transaction records each involving a transaction with the target entity. The application users exclude the candidate application user. Matching validation further includes determining, for each transaction record in the subset, whether a matching transaction record exists in…
DATA DRIFT DETECTION BETWEEN DATA STORAGE
Granted: December 14, 2023
Application Number:
20230401183
A method for detecting data drift between a first database and a second database involves obtaining (from the first database) and based on a change data capture (CDC) event generated in response to a change detected in the first database, a first record identified by the CDC event, obtaining (from the second database) a second record corresponding to the first record, transforming a data structure of the first record from the first database to the data structure of the second database…
END TO END TRAINABLE DOCUMENT EXTRACTION
Granted: December 7, 2023
Application Number:
20230394862
A processor may receive an image and identify a plurality of characters in the image using a machine learning (ML) model. The processor may generate at least one word-level bounding box indicating one or more words including at least a subset of the plurality of characters and/or may generate at least one field-level bounding box indicating at least one field including at least a subset of the one or more words. The processor may overlay the at least one word-level bounding box and the…
ENTITY EXTRACTION WITH ENCODER DECODER MACHINE LEARNING MODEL
Granted: November 30, 2023
Application Number:
20230386236
A method includes executing an encoder machine learning model on multiple token values contained in a document to create an encoder hidden state vector. A decoder machine learning model executing on the encoder hidden state vector generates raw text comprising an entity value and an entity label for each of multiple entities. The method further includes generating a structural representation of the entities directly from the raw text and outputting the structural representation of the…
