Simulating image capture
    3.
    发明授权

    公开(公告)号:US10943107B2

    公开(公告)日:2021-03-09

    申请号:US16590907

    申请日:2019-10-02

    Applicant: INTUIT INC.

    Abstract: The present disclosure relates to simulating the capture of images. In some embodiments, a document and a camera are simulated using a three-dimensional modeling engine. In certain embodiments, a plurality of images are captured of the simulated document from a perspective of the simulated camera, each of the plurality of images being captured under a different set of simulated circumstances within the three-dimensional modeling engine. In some embodiments, a model is trained based at least on the plurality of images which determines at least a first technique for adjusting a set of parameters in a separate image to prepare the separate image for optical character recognition (OCR).

    Conversational user interfaces based on knowledge graphs

    公开(公告)号:US12106013B2

    公开(公告)日:2024-10-01

    申请号:US17449599

    申请日:2021-09-30

    Applicant: INTUIT INC.

    CPC classification number: G06F3/167 G06F16/9024 G06N5/02 G10L15/22 H04L51/02

    Abstract: Certain aspects of the present disclosure provide techniques for executing a function in a software application through a conversational user interface based on a knowledge graph associated with the function. An example method generally includes receiving a request to execute a function in a software application through a conversational user interface. A graph definition of the function is retrieved from a knowledge engine. Input is iteratively requested through the conversational user interface for each parameter of the parameters identified in the graph definition of the function based on a traversal of the graph definition of the function. Based on a completeness graph associated with the function, it is determined that the requested inputs corresponding to the parameters identified in the graph definition of the function have been provided through the conversational user interface. The function is executed using the requested inputs as parameters for executing the function.

    Mapping natural language utterances to nodes in a knowledge graph

    公开(公告)号:US11989214B2

    公开(公告)日:2024-05-21

    申请号:US17513460

    申请日:2021-10-28

    Applicant: INTUIT INC.

    CPC classification number: G06F16/3329 G06F40/30 G06N5/02 G10L15/063

    Abstract: Certain aspects of the present disclosure provide techniques for mapping natural language to stored information. The method generally includes receiving a long-tail query comprising a natural language utterance from a user of an application associated with a set of topics and providing the natural language utterance to a natural language model configured to identify nodes of a knowledge graph. The method further includes, based on output of the natural language model, identifying a node of a knowledge graph associated with the natural language utterance, wherein the output of the natural language model includes a node identifier for the node of the knowledge graph and providing the node identifier to the knowledge engine. The method further includes receiving a response associated with the node of the knowledge graph from the knowledge engine and transmitting the response to the user in response to the long-tail query.

    Combining statistical methods with a knowledge graph

    公开(公告)号:US11436489B2

    公开(公告)日:2022-09-06

    申请号:US16693593

    申请日:2019-11-25

    Applicant: INTUIT INC.

    Abstract: Certain aspects of the present disclosure provide techniques for node matching with accuracy by combining statistical methods with a knowledge graph to assist in responding (e.g., providing content) to a user query in a user support system. In order to provide content, a keyword matching algorithm, statistical method (e.g., a trained BERT model), and data retrieval are each implemented to identify node(s) in a knowledge graph with encoded content relevant to the user's query. The implementation of the keyword matching algorithm, statistical method, and data retrieval results in a matching metric score, semantic score, and graph metric data, respectively. Each score associated with a node is combined to generate an overall score that can be used to rank nodes. Once the nodes are ranked, the top ranking nodes are displayed to the user for selection. Based on the selection, content encoded in the node is displayed to the user.

    Mapping natural language utterances to nodes in a knowledge graph

    公开(公告)号:US11188580B2

    公开(公告)日:2021-11-30

    申请号:US16588873

    申请日:2019-09-30

    Applicant: INTUIT INC.

    Abstract: Certain aspects of the present disclosure provide techniques for mapping natural language to stored information. The method generally includes receiving a long-tail query comprising a natural language utterance from a user of an application associated with a set of topics and providing the natural language utterance to a natural language model configured to identify nodes of a knowledge graph. The method further includes, based on output of the natural language model, identifying a node of a knowledge graph associated with the natural language utterance, wherein the output of the natural language model includes a node identifier for the node of the knowledge graph and providing the node identifier to the knowledge engine. The method further includes receiving a response associated with the node of the knowledge graph from the knowledge engine and transmitting the response to the user in response to the long-tail query.

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