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    DETERMINING EFFICIENT ROUTES IN A COMPLEX SPACE USING HIERARCHICAL INFORMATION AND SPARSE DATA
    13.
    发明公开
    DETERMINING EFFICIENT ROUTES IN A COMPLEX SPACE USING HIERARCHICAL INFORMATION AND SPARSE DATA 审中-公开

    公开(公告)号：US20240005269A1

    公开(公告)日：2024-01-04

    申请号：US17855793

    申请日：2022-07-01

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Benjamin Knight ,  Qi Xi ,  Saumitra Maheshwari ,  Salmaan Ayaz

    IPC: G06Q10/08 ,  G06Q30/06

    CPC classification number: G06Q10/087 ,  G06Q30/0633

    Abstract: An online system performs a method. The method comprises obtaining historical pick data for items located in a warehouse, including data for each of the items picked and pick times between each of the items picked, and determining a taxonomy of items offered by the warehouse. The taxonomy identifies a plurality of product categories structured in a hierarchy, wherein each level of the hierarchy corresponds to a particular level of granularity of product data. The method further comprises applying the historical pick data to a machine learning model to generate pairwise relations between product categories at each level of the taxonomy and generating sequences of product categories based on the pairwise relations. An order for items offered by the warehouse is received and compared to the sequences for each level to generate a pick sequence for picking the items efficiently, which is outputted by the system to a mobile application.

    OPTIMIZATION OF ITEM AVAILABILITY PROMPTS IN THE CONTEXT OF NON-DETERMINISTIC INVENTORY DATA
    14.
    发明公开
    OPTIMIZATION OF ITEM AVAILABILITY PROMPTS IN THE CONTEXT OF NON-DETERMINISTIC INVENTORY DATA 审中-公开

    公开(公告)号：US20230351326A1

    公开(公告)日：2023-11-02

    申请号：US18136513

    申请日：2023-04-19

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Benjamin Knight

    IPC: G06Q10/0875

    CPC classification number: G06Q10/0875

    Abstract: A system receives a request for a set of items at a warehouse from a user device, and determines a set of candidate items responsive to the request. The system applies a trained item availability model to each candidate item to determine a prediction of a likelihood that the candidate item is available for pickup at the warehouse. A subset of candidate items that have a prediction below a threshold is classified as low availability. The computer system also determines a cap of low availability items to present to a user based on a user utility curve. The user utility curve is modeled based on user utility associated with amounts of low availability items presented. The low availability items are filtered to an amount within the determined cap. The filtered low availability items are sent to the user device for presentation in a user interface.

    Optical scanning using receipt imagery for automated tax reconciliation
    15.
    发明授权
    Optical scanning using receipt imagery for automated tax reconciliation 有权

    公开(公告)号：US12260438B2

    公开(公告)日：2025-03-25

    申请号：US17853619

    申请日：2022-06-29

    Applicant: Maplebear Inc.

    Inventor： Benjamin Knight ,  Benjamin Peyrot ,  Djordje Gluhovic ,  Rohit Turumella ,  Alice Han

    IPC: G06Q30/04 ,  G06Q20/20 ,  G06Q40/10 ,  G06Q40/12

    Abstract: An online concierge system requests an image of a receipt of an order from a picker after the picker fulfills the order at a store. The online concierge system performs image processing on the image of the receipt and uses machine learning and optical character recognition to determine a tax amount paid for the order and a confidence score associated with the tax amount. The online concierge system may use the machine learning model for segmenting extracted text in the image of the receipt into tokens. The online concierge system may then determine at least one token associated with a tax item and the tax amount associated with the tax item. The online concierge system communicates the tax amount to the store for reimbursement based on the tax amount and the confidence score.

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