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    DETERMINING RECOMMENDED ITEMS FOR A SHOPPING LIST
    11.
    发明申请
    DETERMINING RECOMMENDED ITEMS FOR A SHOPPING LIST 审中-公开

    公开(公告)号：WO2021133625A1

    公开(公告)日：2021-07-01

    申请号：PCT/US2020/065510

    申请日：2020-12-17

    Applicant: MAPLEBEAR INC. (dba INSTACART)

    Inventor： ARCHAK, Shrikar ,  RAO, Sharath

    IPC: G06Q30/00 ,  G06F16/24578 ,  G06F16/248 ,  G06Q30/0631 ,  G06Q30/0633 ,  G06Q30/0641

    Abstract: In an online concierge system, a customer adds items to an online shopping cart. The online concierge system determines key ingredients from the items in the online shopping cart by mapping the items to generic items and removing non-ingredient items and staple items. The online concierge system retrieves recipes including at least one of the key ingredients. The online concierge system determines complementary ingredients based on the other ingredients in the recipes and calculates co-occurrence scores for the complementary ingredients. Using the co-occurrence scores, the online concierge system ranks the complementary ingredients and sends for display a subset of the complementary ingredients as recommended items.

    POPULATING CATALOG DATA WITH ITEM PROPERTIES BASED ON SEGMENTATION AND CLASSIFICATION MODELS
    13.
    发明申请
    POPULATING CATALOG DATA WITH ITEM PROPERTIES BASED ON SEGMENTATION AND CLASSIFICATION MODELS 审中-公开

    公开(公告)号：WO2020027950A1

    公开(公告)日：2020-02-06

    申请号：PCT/US2019/039075

    申请日：2019-06-25

    Applicant: MAPLEBEAR INC. (DBA INSTACART)

    Inventor： HSIEH, Jonathan ,  GOTHE, Oliver ,  STANLEY, Jeremy

    IPC: G06K9/46 ,  G06K9/66 ,  G06T7/00

    Abstract: A method for populating an inventory catalog includes receiving an image showing an item in the inventory catalog and comprising a plurality of pixels. A machine learned segmentation neural network is retrieved to determine location of pixels in an image that are associated with an image label and the property. The method determines a subset of pixels associated with the item label in the received image and identifies locations of the subset of pixels of the received image, and extracts the subset of pixels from the received image. The method retrieves a machine learned classifier to determine whether an image shows the item label. The method determines, using the machine learned classifier, that the extracted subset of pixels shows the item label. The method updates the inventory catalog for the item to indicate that the item has the property associated with the item label.

    ENABLING ORDERING THROUGH A CLIENT APPLICATION THROUGH TEXT MESSAGES WHEN A CLIENT DEVICE LACKS A DATA CONNECTION TO A NETWORK
    18.
    发明申请
    ENABLING ORDERING THROUGH A CLIENT APPLICATION THROUGH TEXT MESSAGES WHEN A CLIENT DEVICE LACKS A DATA CONNECTION TO A NETWORK 有权

    公开(公告)号：US20250005650A1

    公开(公告)日：2025-01-02

    申请号：US18217337

    申请日：2023-06-30

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Muhammad Iftekher Chowdhury

    IPC: G06Q30/0601 ,  H04L51/046 ,  H04W12/033

    Abstract: An online concierge system provides a client application executed on a client device for customers to generate orders for fulfillment by the online concierge system. If the client device is unable to establish a data connection to a network, the client application locally caches data on the client device for one or more retailers that includes items that have been previously purchased by the customer or that are popular among customers. The customer generates an order through the client application for a retailer based on the locally cached items for the retailer. The online concierge system application generates an encrypted text message based on the order that is transmitted to the online concierge system via short message service (SMS). The online concierge system may also return messages via SMS, which may be presented by the client application.

    USING UNSUPERVISED CLUSTERING AND LANGUAGE MODEL TO NORMALIZE ATTRIBUTE TUPLES OF ITEMS IN A DATABASE
    19.
    发明申请
    USING UNSUPERVISED CLUSTERING AND LANGUAGE MODEL TO NORMALIZE ATTRIBUTE TUPLES OF ITEMS IN A DATABASE 有权

    公开(公告)号：US20250005279A1

    公开(公告)日：2025-01-02

    申请号：US18215505

    申请日：2023-06-28

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Shih-Ting Lin ,  Prithvishankar Srinivasan ,  Saurav Manchanda ,  Shishir Kumar Prasad ,  Min Xie

    IPC: G06F40/247 ,  G06F16/21 ,  G06F16/215 ,  G06F16/28

    Abstract: A computer system uses clustering and a large language model (LLM) to normalize attribute tuples for items stored in a database of an online system. The online system collects attribute tuples, each attribute tuple comprising an attribute type and an attribute value for an item. The online system initially clusters the attribute tuples into a first plurality of clusters. The online system generates prompts for input into the LLM, each prompt including a subset of attribute tuples grouped into a respective cluster of the first plurality. Based on the prompts, the LLM generates a second plurality of clusters, each cluster including one or more attribute tuples that have a common attribute type and a common attribute value. The online system maps each attribute tuple to a respective normalized attribute tuple associated with each cluster. The online system rewrites each attribute tuple in the database to a corresponding normalized attribute tuple.

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