Intuit Patent Applications

INPUT NORMALIZATION FOR MODEL BASED RECOMMENDATION ENGINES

Granted: March 21, 2024
Application Number: 20240095777
In one or more embodiments, transaction data between multiple users and multiple merchants is retrieved. The retrieved transaction data is aggregated for each of the multiple users and each of the multiple merchants. The aggregated data may then be normalized. An example normalization process may include income normalization, where a user's total transaction amount at a particular merchant is normalized by the user's income. Other forms of normalization may also be employed. Using the…

SYSTEM AND METHOD FOR SCHEDULING TASKS

Granted: February 29, 2024
Application Number: 20240070584
A method comprising generating, during multiple user sessions of a first user with a software application, first clickstream data from the multiple user sessions, and extracting, from the first clickstream data, a first plurality of task instances of the first user performing a first plurality of tasks. The method also includes decomposing, from the first clickstream data, each task instance of the first plurality of task instances into a first plurality of steps to obtain a first…

SYSTEM AND METHOD FOR SPATIAL ENCODING AND FEATURE GENERATORS FOR ENHANCING INFORMATION EXTRACTION

Granted: February 15, 2024
Application Number: 20240054802
A system and method for extracting data from a piece of content using spatial information about the piece of content. The system and method may use a conditional random fields process or a bidirectional long short term memory and conditional random fields process to extract structured data using the spatial information.

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…

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…

METHODS AND SYSTEMS FOR GENERATING PROBLEM DESCRIPTION

Granted: February 1, 2024
Application Number: 20240037342
A computing system identifies an incoming voice call from a user device to an agent device associated with the computing system. The computing system generates a transcription of the incoming voice call using one or more natural language processing techniques. The computing system extracts a problem description from the transcription. The problem description indicates a topic for the incoming voice call. A first machine learning model estimates a situation vector from the problem…

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…

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…

METHODS AND SYSTEMS FOR GENERATING PROBLEM DESCRIPTION

Granted: February 1, 2024
Application Number: 20240037342
A computing system identifies an incoming voice call from a user device to an agent device associated with the computing system. The computing system generates a transcription of the incoming voice call using one or more natural language processing techniques. The computing system extracts a problem description from the transcription. The problem description indicates a topic for the incoming voice call. A first machine learning model estimates a situation vector from the problem…

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.

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.

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.