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    Automation engine using a hyperparameter learning model to optimize sub-systems of an online system
    1.
    发明授权
    Automation engine using a hyperparameter learning model to optimize sub-systems of an online system 有权

    公开(公告)号：US12271939B2

    公开(公告)日：2025-04-08

    申请号：US17855788

    申请日：2022-06-30

    Applicant: Maplebear Inc.

    Inventor： Sonali Deepak Chhabria ,  Xiangyu Wang ,  Aman Jain ,  Ganesh Krishnan ,  Trace Levinson ,  Jian Wang

    IPC: G06Q30/0601 ,  G01C21/34 ,  G06Q10/0631 ,  G06Q10/0637 ,  G06Q10/087

    Abstract: An online concierge system includes a marketplace automation engine for setting various control parameters affecting marketplace operation. The marketplace automation engine applies a hyperparameter learning model to the marketplace state data to predict a set of hyperparameters affecting a set of respective parameterized control decision models. The hyperparameter learning model is trained on historical marketplace state data and a configured outcome objective for the online concierge system. The marketplace automation engine independently applies the set of parameterized control decision models to the marketplace state data using the hyperparameters to generate a respective set of control parameters affecting marketplace operation of the online concierge system. The marketplace automation engine applies the respective set of control parameters to operation of the online concierge system.

    Using Computer Models to Predict Delivery Times for an Order During Creation of the Order
    3.
    发明申请
    Using Computer Models to Predict Delivery Times for an Order During Creation of the Order 有权

    公开(公告)号：US20250104003A1

    公开(公告)日：2025-03-27

    申请号：US18475766

    申请日：2023-09-27

    Applicant: Maplebear Inc.

    Inventor： Shuai Wang ,  Zi Wang ,  Liang Chen ,  Aman Jain ,  Xiangyu Wang ,  Jian Wang

    IPC: G06Q10/0834 ,  G06Q30/0601

    Abstract: One or more trained computer models are used to determine, at different stages of an order, an estimated time range for delivery of the order at an online system. The online system retrieves a set of candidate ranges of delivery times for the order. The online system applies the one or more computer models trained to predict a value of a metric for each candidate range in the set of candidate ranges, based on one or more features associated with the order. The online system selects a range of delivery times for the order from the set of candidate ranges, based on the predicted value of the metric for each candidate range. The online system causes a device of the user to display a user interface with the selected range of delivery times for the order.

    Generating a range of estimated fulfillment times for an order based on characteristics of an order
    4.
    发明授权
    Generating a range of estimated fulfillment times for an order based on characteristics of an order 有权

    公开(公告)号：US12033109B1

    公开(公告)日：2024-07-09

    申请号：US18114858

    申请日：2023-02-27

    Applicant: Maplebear Inc.

    Inventor： Shuai Wang ,  Zi Wang ,  Liang Chen ,  Houtao Deng ,  Xiangyu Wang ,  Aman Jain ,  Jian Wang

    IPC: G06Q10/0835 ,  G06Q10/0833

    CPC classification number: G06Q10/0835 ,  G06Q10/0833

    Abstract: An online concierge system delivers items from retailers to customers. The online concierge predicts a range of times during which an order may be fulfilled for presentation to a user. The online concierge system uses a trained maximum time prediction model to determine a maximum time for order fulfillment based on an order. A trained minimum time prediction model determines a minimum time for order fulfillment from the order and the maximum time. The minimum time may account for one or more rules (e.g., a percentage of orders fulfilled before the minimum time, a desired rate of selection of a range including the minimum time). A range bounded by the maximum time and the minimum time is transmitted to a customer to enable the customer to select a time interval for order fulfillment.

    SELECTING ORDER CHECKOUT OPTIONS
    7.
    发明公开
    SELECTING ORDER CHECKOUT OPTIONS 审中-公开

    公开(公告)号：US20240144355A1

    公开(公告)日：2024-05-02

    申请号：US17977712

    申请日：2022-10-31

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Liang Chen ,  Aman Jain ,  Xiangyu Wang ,  Houtao Deng ,  Jae Cho

    IPC: G06Q30/06 ,  G06Q30/02

    CPC classification number: G06Q30/0641 ,  G06Q30/0201 ,  G06Q30/0607

    Abstract: The present disclosure is directed to selecting order checkout options. In particular, the methods and systems of the present disclosure may, responsive to receiving data describing a potential order for an online shopping concierge platform: generate, based at least in part on the data describing the potential order, a plurality of different and distinct checkout options for the potential order; determine, for each checkout option of the plurality of different and distinct checkout options and based at least in part on one or more machine learning (ML) models, a probability that a customer associated with the potential order will proceed with the potential order if presented with the checkout option; and select a subset of checkout options for presentation to the customer based on their respective determined probabilities that the customer will proceed with the potential order if presented with the subset of checkout options.

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