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    SYSTEMS AND METHODS OF BUSINESS CATEGORIZATION AND SERVICE RECOMMENDATION
    3.
    发明申请
    SYSTEMS AND METHODS OF BUSINESS CATEGORIZATION AND SERVICE RECOMMENDATION 有权

    公开(公告)号：US20210241331A1

    公开(公告)日：2021-08-05

    申请号：US16779781

    申请日：2020-02-03

    Applicant: Intuit Inc.

    Inventor： Erez Katzenelson ,  Elik Sror ,  Shlomi Medalion ,  Shimon Shahar ,  Shir Meir Lador ,  Sigalit Bechler ,  Alexander Zhicharevich ,  Onn Bar

    IPC: G06Q30/04 ,  G06Q10/06 ,  G06N3/04

    Abstract: In one aspect, the present disclosure relates to a method of generating business descriptions performed by a server, said method may include: receiving a plurality of invoices, each invoice being associated with a business of a plurality of businesses; extracting a plurality of texts from the plurality of invoices; embedding the plurality of texts to a vector space to obtain a plurality of invoice vectors; generating a plurality of clusters in the vector space, each cluster of the plurality of clusters comprising at least one invoice vector of the plurality of invoice vectors; generating a description for a cluster, the description for the cluster representing all invoice vectors assigned to the cluster; for each business of the plurality of businesses that has at least one invoice vector assigned to the cluster, associating the business with the description; and indexing the plurality of businesses within a database by the generated descriptions.

    SYSTEMS AND METHODS OF BUSINESS CATEGORIZATION AND SERVICE RECOMMENDATION
    4.
    发明申请
    SYSTEMS AND METHODS OF BUSINESS CATEGORIZATION AND SERVICE RECOMMENDATION 有权

    公开(公告)号：US20210241072A1

    公开(公告)日：2021-08-05

    申请号：US16779785

    申请日：2020-02-03

    Applicant: Intuit Inc.

    Inventor： Erez Katzenelson ,  Elik Sror ,  Shlomi Medalion ,  Shimon Shahar ,  Shir Meir Lador ,  Sigalit Bechler ,  Alexander Zhicharevich ,  Onn Bar

    IPC: G06N3/04 ,  G06F16/9535 ,  G06N3/08

    Abstract: A method for recommending offerings to a business may include: receiving a request for recommended business offerings from a device; receiving business data associated with a business from the device, the business data comprising invoice data associated with the business; embedding the business data to a vector space to obtain a business vector, the vector space comprising a plurality of other vectors associated with other businesses; calculating a relation metric between the business vector and a vector of the plurality of other vectors, the vector being associated with a second business, the relation metric representing a degree of relation between the business and the second business; determining that the relation metric is above a pre-defined threshold value; and responsive to the determining, sending business data associated with the second business to the device, the business data associated with the second business comprising invoice data associated with the second business.

    System, method, and computer-readable medium for capacity-constrained recommendation
    5.
    发明授权
    System, method, and computer-readable medium for capacity-constrained recommendation 有权

    公开(公告)号：US11551282B2

    公开(公告)日：2023-01-10

    申请号：US16940087

    申请日：2020-07-27

    Applicant: Intuit Inc.

    Inventor： Shlomi Medalion ,  Sigalit Bechler ,  Oren Sar Shalom ,  Guy Maman

    IPC: G06Q30/00 ,  G06Q30/06 ,  G06F16/9536

    Abstract: This disclosure provides systems, methods and apparatuses for recommending items to users of a recommendation system. In some implementations, the recommendation system determines a plurality of contribution values based on interactions between a plurality of users and a plurality of items. Each of the plurality of contribution values represents a confidence level that a respective user prefers a respective item. The recommendation system further determines a capacity of each of the plurality of items. The capacity of each item represents a maximum number of users to which the item can be recommended. The recommendation system recommends one or more items of the plurality of items to each of the plurality of users based at least in part on the plurality of contribution values and the capacities of the plurality of items.

    CAPACITY-CONSTRAINED RECOMMENDATION SYSTEM
    6.
    发明申请
    CAPACITY-CONSTRAINED RECOMMENDATION SYSTEM 有权

    公开(公告)号：US20220027975A1

    公开(公告)日：2022-01-27

    申请号：US16940087

    申请日：2020-07-27

    Applicant: Intuit Inc.

    Inventor： Shlomi Medalion ,  Sigalit Bechler ,  Oren Sar Shalom ,  Guy Maman

    IPC: G06Q30/06 ,  G06F16/9536

    Abstract: This disclosure provides systems, methods and apparatuses for recommending items to users of a recommendation system. In some implementations, the recommendation system determines a plurality of contribution values based on interactions between a plurality of users and a plurality of items. Each of the plurality of contribution values represents a confidence level that a respective user prefers a respective item. The recommendation system further determines a capacity of each of the plurality of items. The capacity of each item represents a maximum number of users to which the item can be recommended. The recommendation system recommends one or more items of the plurality of items to each of the plurality of users based at least in part on the plurality of contribution values and the capacities of the plurality of items.

    LOGISTIC RECOMMENDATION ENGINE
    7.
    发明申请
    LOGISTIC RECOMMENDATION ENGINE 有权

    公开(公告)号：US20210334748A1

    公开(公告)日：2021-10-28

    申请号：US16861157

    申请日：2020-04-28

    Applicant: Intuit Inc.

    Inventor： Yair Horesh ,  Yehezkel Shraga Resheff ,  Adi Shalev ,  Shlomi Medalion ,  Elik Sror ,  Miriam Hanna Manevitz ,  Sigalit Bechler

    IPC: G06Q10/08 ,  G06N20/00

    Abstract: A method may include receiving, for a package, shipment details including attributes, obtaining, for a subset of the attributes, logistic preferences, applying the logistic preferences to the shipment details to obtain modified shipment details, training a classifier using shipment transactions each including values for the attributes and labeled with a vendor logistic service, generating, by applying the classifier to the modified shipment details, scores for vendor logistic services, and recommending a vendor logistic service from the vendor logistic services using the scores.

    TRANSACTION ENTITY PREDICTION WITH A GLOBAL LIST
    8.
    发明申请
    TRANSACTION ENTITY PREDICTION WITH A GLOBAL LIST 有权

    公开(公告)号：US20240419985A1

    公开(公告)日：2024-12-19

    申请号：US18637860

    申请日：2024-04-17

    Applicant: Intuit, Inc.

    Inventor： Hadar Lackritz ,  Natalie Bar Eliyahu ,  Omer Wosner ,  Sigalit Bechler

    IPC: G06N5/022 ,  G06F40/174 ,  G06N20/00

    Abstract: Certain aspects of the disclosure pertain to predicting a candidate entity match for a transaction with a machine learning model. A description of a transaction comprising encoded transaction data associated with an organization is received as input. In response, at least one machine learning model can be invoked to infer a transaction embedding based on the description, a first score that captures similarity between the transaction embedding entity embeddings associated with a global list of entities and organizations, a second score that captures a probability of interaction between the first organization and the entities based on organization and entity embeddings that capture profile data associated with the organization and the entities, and at least one candidate entity based on the first score and the second score. Finally, the inferred candidate entity can be output for use by an automated data entry or other process or system.

    Machine learning technique with targeted feature sets for categorical anomaly detection
    10.
    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.

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