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    Machine learning technique with targeted feature sets for categorical anomaly detection
    102.
    发明授权
    Machine learning technique with targeted feature sets for categorical anomaly detection 有权

    公开(公告)号：US11741486B1

    公开(公告)日：2023-08-29

    申请号：US17804621

    申请日：2022-05-31

    Applicant: INTUIT INC.

    Inventor： Natalie Bar Eliyahu ,  Sigalit Bechler ,  Gilad Uziely

    IPC: G06N5/02 ,  G06Q30/0201 ,  G06Q40/12

    CPC classification number: G06Q30/0201 ,  G06Q40/12

    Abstract: Aspects of the present disclosure provide techniques for categorical anomaly detection. Embodiments include receiving values for a plurality of data categories for an entity of a plurality of entities. Embodiments include generating a feature vector for the entity based on the values, the feature vector excluding a first value for a first data category of the plurality of data categories. Embodiments include providing one or more inputs to a machine learning model based on the feature vector and determining, based on one or more outputs received from the machine learning model, one or more other entities of the plurality of entities that are grouped with the entity. Embodiments include determining that the first value is anomalous based on respective values for the first data category for the one or more other entities. Embodiments include performing one or more actions based on the determining that the first value is anomalous.

    Application recommendation machine learning system
    103.
    发明授权
    Application recommendation machine learning system 有权

    公开(公告)号：US11741358B2

    公开(公告)日：2023-08-29

    申请号：US16791380

    申请日：2020-02-14

    Applicant: INTUIT INC.

    Inventor： Runhua Zhao ,  Naveen Rajendrapandian ,  Chris J. Wang

    IPC: G06N3/08 ,  G06F16/9535 ,  G06N3/045

    CPC classification number: G06N3/08 ,  G06F16/9535 ,  G06N3/045

    Abstract: Certain aspects of the present disclosure provide techniques for generating a recommendation of third-party applications to a user by a recommendation engine. The recommendation engine includes two deep-learning models that use various data sources (e.g., user data and application data) to generate the recommendation. One deep-learning model generates a relevance score for each available third-party application. The relevance score is used to determine a relevant application(s). The other deep-learning model generates a connection score for each relevant application. The recommendation engine uses the relevance score and the connections to generate an engagement score for each relevant application to determine whether the user would use the third-party application if recommended to the user. Those relevant applications with an engagement score that meet pre-determined criteria are determined and displayed to the user in the application as a recommendation.

    System and method for identifying questions of users of a data management system
    105.
    发明授权
    System and method for identifying questions of users of a data management system 有权

    公开(公告)号：US11734314B2

    公开(公告)日：2023-08-22

    申请号：US17379832

    申请日：2021-07-19

    Applicant: Intuit Inc.

    Inventor： Steven J. Brown

    IPC: G06F16/28 ,  G06F16/93 ,  G06Q40/12

    CPC classification number: G06F16/285 ,  G06F16/93 ,  G06Q40/123

    Abstract: Systems and methods are disclosed. An example method may be performed by one or more processors of a system and include retrieving case data indicating, for each respective case of a number of cases, one or more documents retrieved to assist a system user associated with the respective case, generating, from the case data, a case matrix including a plurality of rows each corresponding to a respective case of the number of cases and a plurality of columns each corresponding to the documents retrieved to assist the system user associated with the respective case, and identifying groups of similar cases among the plurality of cases based on a clustering process performed on at least a portion of the case matrix.

    Text feature guided visual based document classifier
    107.
    发明授权
    Text feature guided visual based document classifier 有权

    公开(公告)号：US11720605B1

    公开(公告)日：2023-08-08

    申请号：US17876069

    申请日：2022-07-28

    Applicant: Intuit Inc.

    Inventor： Tharathorn Rimchala ,  Yingxin Wang

    IPC: G06F16/28 ,  G06V30/14 ,  G06F16/93 ,  G06F16/2457

    CPC classification number: G06F16/287 ,  G06F16/24578 ,  G06F16/93 ,  G06V30/1444

    Abstract: 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 or more visual features. The one or more visual features are generated by the student classification model that is trained based on important text identified by a teacher classification model for the one or more document types, with the teacher classification model being a text-based classification model. Generating training data and training the student classification model based on the training data are also described.

    SYSTEM AND METHOD FOR ASSOCIATING LOGS TO REPOSITORIES USING SOURCE CODE
    108.
    发明公开
    SYSTEM AND METHOD FOR ASSOCIATING LOGS TO REPOSITORIES USING SOURCE CODE 审中-公开

    公开(公告)号：US20230244474A1

    公开(公告)日：2023-08-03

    申请号：US17589653

    申请日：2022-01-31

    Applicant: Intuit Inc.

    Inventor： Elad Shmidov ,  Margarita Vald ,  Yerucham Meir Berkowitz ,  Boaz Sapir ,  Liron London ,  Dan Sharon ,  Vadim Belov

    IPC: G06F8/70

    CPC classification number: G06F8/70

    Abstract: A method includes receiving event strings from source code repositories, creating, for the source code repositories, digests of keywords, receiving log strings, and aggregating the log strings into a log group. The method further includes comparing the digests to the log group to generate scores, whereby the scores correlate the digests to the log group. The method further includes selecting a source code repository from the source code repositories according to the scores, and associating the log group to a service corresponding to the source code repository, where the source code repository corresponds to the digest with a highest score.

    Method for serving parameter efficient NLP models through adaptive architectures
    109.
    发明授权
    Method for serving parameter efficient NLP models through adaptive architectures 有权

    公开(公告)号：US11704602B2

    公开(公告)日：2023-07-18

    申请号：US16732869

    申请日：2020-01-02

    Applicant: Intuit Inc.

    Inventor： Terrence J. Torres ,  Tharathorn Rimchala ,  Andrew Mattarella-Micke

    IPC: G06F40/126 ,  G06N20/20 ,  G06F40/284

    CPC classification number: G06N20/20 ,  G06F40/126 ,  G06F40/284

    Abstract: A machine learning system executed by a processor may generate predictions for a variety of natural language processing (NLP) tasks. The machine learning system may include a single deployment implementing a parameter efficient transfer learning architecture. The machine learning system may use adapter layers to dynamically modify a base model to generate a plurality of fine-tuned models. Each fine-tuned model may generate predictions for a specific NLP task. By transferring knowledge from the base model to each fine-tuned model, the ML system achieves a significant reduction in the number of tunable parameters required to generate a fine-tuned NLP model and decreases the fine-tuned model artifact size. Additionally, the ML system reduces training times for fine-tuned NLP models, promotes transfer learning across NLP tasks with lower labeled data volumes, and enables easier and more computationally efficient deployments for multi-task NLP.

    Universal report engine
    110.
    发明授权
    Universal report engine 有权

    公开(公告)号：US11698912B2

    公开(公告)日：2023-07-11

    申请号：US17139659

    申请日：2020-12-31

    Applicant: Intuit Inc.

    Inventor： Jayanth Saimani ,  Ajay Karthik Nama Nagaraj

    IPC: G06F16/00 ,  G06F16/248 ,  G06F16/22 ,  G06F16/245

    CPC classification number: G06F16/248 ,  G06F16/2246 ,  G06F16/245

    Abstract: A method involves receiving a first command. The first command includes a data extraction expression applied to fields of a dataset of a data source. The first command also includes a first report configuration expression applied to first dimensions of a first report. The method also involves generating, by executing the data extraction expression on the dataset, records of the dataset. The method also involves generating, by executing the first report configuration expression on the records, a first tree of subsets of the records. The method also involves populating, using the first report configuration expression and the first tree of subsets, cells of the first dimensions to obtain first populated dimensions. The method also involves generating, in response to receiving the first command and by traversing the first tree of subsets, the first report including the first populated dimensions.

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