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    USING TRANSFER LEARNING TO REDUCE DISCREPANCY BETWEEN TRAINING AND INFERENCE FOR A MACHINE LEARNING MODEL
    94.
    发明公开
    USING TRANSFER LEARNING TO REDUCE DISCREPANCY BETWEEN TRAINING AND INFERENCE FOR A MACHINE LEARNING MODEL 审中-公开

    公开(公告)号：US20230162038A1

    公开(公告)日：2023-05-25

    申请号：US17534184

    申请日：2021-11-23

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Peng Qi ,  Zhenbang Chen

    IPC: G06N3/08 ,  G06N3/04 ,  G06Q30/02

    CPC classification number: G06N3/084 ,  G06N3/04 ,  G06Q30/0202

    Abstract: An online system uses a trained model predicting likelihoods of a user performing a specific interaction with items to order or to rank items for display to the user. The online system trains the model using interactions by users with items displayed by the online system. However, selection, popularity, and position from display of the items affects the model during training. To improve the model, the online system further trains the model using additional training data obtained from displaying items to users in different orders. The further training is done on a limited portion of the model, such as a limited number of layers of the model, to improve the model performance while reducing an amount of additional data to acquire to further train the model.

    PREDICTIVE INVENTORY AVAILABILITY
    96.
    发明申请
    PREDICTIVE INVENTORY AVAILABILITY 有权

    公开(公告)号：US20230113122A1

    公开(公告)日：2023-04-13

    申请号：US18080118

    申请日：2022-12-13

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Sharath Rao ,  Shishir Prasad ,  Jeremy Stanley

    IPC: G06Q10/087 ,  G06Q10/0631 ,  G06Q10/067

    Abstract: A method for predicting inventory availability, involving receiving a delivery order including a plurality of items and a delivery location, and identifying a warehouse for picking the plurality of items. The method retrieves a machine-learned model that predicts a probability that an item is available at the warehouse. The machine-learned model is trained, using machine learning, based in part on a plurality of datasets. The plurality of datasets include data describing items included in previous delivery orders, whether each item in each previous delivery order was picked, a warehouse associated with each previous delivery order, and a plurality of characteristics associated with each of the items. The method predicts the probability that one of the plurality of items in the delivery order is available at the warehouse, and generates an instruction to a picker based on the probability. An instruction is transmitted to a mobile device of the picker.

    PICKING SEQUENCE OPTIMIZATION WITHIN A WAREHOUSE FOR AN ITEM LIST
    97.
    发明申请
    PICKING SEQUENCE OPTIMIZATION WITHIN A WAREHOUSE FOR AN ITEM LIST 有权

    公开(公告)号：US20230062937A1

    公开(公告)日：2023-03-02

    申请号：US17458127

    申请日：2021-08-26

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Xinyu Li ,  Haixun Wang ,  Ruoming Jin

    IPC: G06Q10/06 ,  G06Q30/06 ,  G06Q10/04 ,  G06Q10/08 ,  G06F16/901

    Abstract: An online concierge system generates a suggested picking sequence to reduce the amount of time for a shopper to fulfill an online order of items from a warehouse. The online concierge system determines an average amount of time to sequentially pick items between different aisle pairs for a warehouse based on timestamps from item fulfillment in historical orders. The system generates a distance graph including aisle nodes connected by edges representing the pairwise distance between aisles. The system solves a traveling salesperson problem to generate a ranked order of aisle nodes for each of the historical orders. The system generates a ranked global sequence of aisle nodes based on the plurality of ranked orders of aisle nodes. The system applies the ranked global sequence to new delivery orders to generate the suggested picking sequence for a shopper.

    VERIFYING MATCHES BETWEEN IDENTIFIERS STORED IN A DIGITAL CATALOG
    98.
    发明申请
    VERIFYING MATCHES BETWEEN IDENTIFIERS STORED IN A DIGITAL CATALOG 有权

    公开(公告)号：US20230055163A1

    公开(公告)日：2023-02-23

    申请号：US17407079

    申请日：2021-08-19

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Gordon McCreight ,  Alex Charlton

    IPC: G06Q30/00 ,  G06Q10/08 ,  G06F16/2458

    Abstract: An online system receives an identification code for a product from a third party, which includes attributes that the third party uses to identify the product. The online system normalizes the identification code according to a set of guidelines received from the third party. The normalized identification code resembles previous identification codes received from the third party. The online system identifies a cluster of identification codes that represents the product identified by the normalized identification code by applying a set of matching rules to the normalized identification code and updates the identified cluster of identification codes to include the normalized identification code. The online system identifies a universal product identifier that represents the product of the cluster of the cluster of identification codes and stores the universal product identifier with the updated cluster of identification code.

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