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    MACHINE LEARNING MODEL FOR CLICK THROUGH RATE PREDICTION USING THREE VECTOR REPRESENTATIONS
    52.
    发明申请
    MACHINE LEARNING MODEL FOR CLICK THROUGH RATE PREDICTION USING THREE VECTOR REPRESENTATIONS 有权

    公开(公告)号：US20230135683A1

    公开(公告)日：2023-05-04

    申请号：US17513739

    申请日：2021-10-28

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Ramasubramanian Balasubramanian ,  Saurav Manchanda

    IPC: G06Q30/06 ,  G06Q30/02

    Abstract: An online concierge system uses a machine learning click through rate model to select promoted items based on user embeddings, item embeddings, and search query embeddings. Embeddings obtained by an embedding model may be used as inputs to the click through rate model. The embedding model may be trained using different actions to score the strength of a customer interaction with an item. For example, a customer purchasing an item may be a stronger signal than a customer placing an item in a shopping cart, which in turn may be a stronger signal than a customer clicking on an item. The online concierge system generates a ranking of candidate promoted items based on the search query and using the click through rate model. Based on the ranking, the online concierge system displays promoted items along with the organic search results to the customer.

    RECEIPT CONTENT CAPTURE DEVICE FOR INVENTORY TRACKING
    53.
    发明申请
    RECEIPT CONTENT CAPTURE DEVICE FOR INVENTORY TRACKING 有权

    公开(公告)号：US20230091975A1

    公开(公告)日：2023-03-23

    申请号：US18071649

    申请日：2022-11-30

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Robert Russel Adams

    IPC: G06Q10/08 ,  G06F16/25 ,  G06Q20/20 ,  G06Q40/00 ,  G06Q20/04

    Abstract: A receipt capture device can collect transaction information from transactions conducted at a point of sale system by capturing receipt data transmitted from the point of sale system for the purpose of printing receipts at an external receipt printer. The receipt capture device can then send the collected receipt data to an online system for analysis. At the online system, received receipt data can be decoded from the printer-readable format it is transmitted in and used to enhance the online system's understanding of transactions occurring at a retailer associated with the point of sale system. For example, the online system can determine an approximate inventory of items available at purchase at the retailer by aggregating items recently purchased in transactions at the point of sale system.

    TRAINING A MODEL TO PREDICT TRAVEL DISTANCE BETWEEN TWO GEOGRAPHIC LOCATIONS
    56.
    发明申请
    TRAINING A MODEL TO PREDICT TRAVEL DISTANCE BETWEEN TWO GEOGRAPHIC LOCATIONS 有权

    公开(公告)号：US20220391965A1

    公开(公告)日：2022-12-08

    申请号：US17338421

    申请日：2021-06-03

    Applicant: Maplebear, Inc.(dba Instacart)

    Inventor： Jagannath Putrevu ,  Reza Faturechi

    IPC: G06Q30/06 ,  G06Q10/08 ,  G01C21/20 ,  G06K9/62 ,  G06N3/08

    Abstract: An online concierge system receives orders from users and assigns orders to shoppers for fulfillment. Each order specifies a destination location and a warehouse from which items in the order are obtained. When assigning orders to shoppers, the online concierge system seeks to minimize distances traveled by shoppers fulfilling orders. To more efficiently assign orders to shoppers, the online concierge system trains a distance prediction model to predict a distance traveled between a starting location and a destination location from the starting location, the destination location, and a Haversine distance between the destination location and the starting location. Information identifying distances traveled by shoppers when fulfilling previous orders or information about distances between locations from a third party system may be used to train the distance prediction model.

    OVERLAP DETECTION FOR AN ITEM RECOGNITION SYSTEM
    57.
    发明申请
    OVERLAP DETECTION FOR AN ITEM RECOGNITION SYSTEM 有权

    公开(公告)号：US20220343308A1

    公开(公告)日：2022-10-27

    申请号：US17726389

    申请日：2022-04-21

    Applicant: Maplebear Inc. (dba Instacart)

    Inventor： Shiyuan Yang ,  Shray Chandra

    IPC: G06Q20/20 ,  H04N5/247 ,  G06V10/22 ,  G06V10/10 ,  G06V10/70 ,  G06T7/50 ,  G06V10/94 ,  G06V20/60 ,  G06Q20/18 ,  G01G19/414

    Abstract: An item recognition system uses a top camera and one or more peripheral cameras to identify items. The item recognition system may use image embeddings generated based on images captured by the cameras to generate a concatenated embedding that describes an item depicted in the image. The item recognition system may compare the concatenated embedding to reference embeddings to identify the item. Furthermore, the item recognition system may detect when items are overlapping in an image. For example, the item recognition system may apply an overlap detection model to a top image and a pixel-wise mask for the top image to detect whether an item is overlapping with another in the top image. The item recognition system notifies a user of the overlap if detected.

    CLUSTERING ITEMS OFFERED BY AN ONLINE CONCIERGE SYSTEM TO CREATE AND TO RECOMMEND COLLECTIONS OF ITEMS TO USERS
    58.
    发明申请
    CLUSTERING ITEMS OFFERED BY AN ONLINE CONCIERGE SYSTEM TO CREATE AND TO RECOMMEND COLLECTIONS OF ITEMS TO USERS 有权

    公开(公告)号：US20220335489A1

    公开(公告)日：2022-10-20

    申请号：US17232621

    申请日：2021-04-16

    Applicant: Maplebear, Inc.(dba Instacart)

    Inventor： Sharath Rao Karikurve ,  Angadh Singh

    IPC: G06Q30/06 ,  G06N20/00 ,  G06F17/16

    Abstract: An online concierge system maintains information about items offered for purchase and users of the online concierge system. Based on prior purchases of items by users, the online concierge system trains a model to determine a likelihood of a user purchasing an item based on an embedding for the object and embedding for the user. The online concierge system identifies a collection of items and generates an embedding for the collection. The collection may be a cluster of items determined from similarities between embeddings of items. Alternatively, the collection may be a group of items having a common category. The online concierge system includes one or more collections of items along with individual items when recommending items for the users, so the trained model is applied to embeddings of the individual items and to embeddings of the one or more collections to generate recommendations for a user.

    MAPPING RECIPE INGREDIENTS TO PRODUCTS
    59.
    发明申请
    MAPPING RECIPE INGREDIENTS TO PRODUCTS 有权

    公开(公告)号：US20220292568A1

    公开(公告)日：2022-09-15

    申请号：US17196879

    申请日：2021-03-09

    Applicant: Maplebear, Inc. (dba Instacart)

    Inventor： William Silverthorne Faurot, III ,  Tyler Russell Tate

    IPC: G06Q30/06 ,  G06N20/00 ,  G06F16/2457

    Abstract: An online system receives a recipe from a customer mobile device. The online system performs natural language processing on the recipe to determine parsed ingredients. For each of one or more of the determined parsed ingredients, the online system maps the parsed ingredient to a generic item. The online system queries a product database with the mapped generic item to obtain one or more products associated with the mapped generic item. The online system applies a machine-learned conversion model to each of the one or more products to determine a conversion likelihood for the product. The conversion model may be trained based on historical data describing previous conversions made by customers presented with an opportunity to add products to an order. The online system selects a product from the one or more products based on the determined conversion likelihoods and adds the selected product to an order.

    CERTIFIED DELIVERIES OF HIGH-VALUE ITEMS
    60.
    发明申请
    CERTIFIED DELIVERIES OF HIGH-VALUE ITEMS 有权

    公开(公告)号：US20220261744A1

    公开(公告)日：2022-08-18

    申请号：US17178183

    申请日：2021-02-17

    Applicant: Maplebear, Inc. (DBA Instacart)

    Inventor： Anastasija Kovalova ,  Neera Chatterjee

    IPC: G06Q10/08 ,  G06F21/31

    Abstract: An online system receives, from a customer mobile application (CMA) an order including a high-value item determines that the order includes the high-value item. The online system transmits an indication that the order includes the high-value item to a delivery mobile application (DMA). The DMA transmits a real-time location of a client device of a delivery agent to the online system. Responsive to determining that the delivery agent is at a delivery location, the online system transmits an indication to the DMA to display a user interface including an interactive element for requesting a signature from a customer. Responsive to receiving an indication of an interaction with the interactive element, the online system transmits an indication to the CMA to display a user interface with a signature element. The CMA transmits a signature received via the signature element to the online system, which stores the signature as verification information.

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