公开(公告)号：US20220114640A1

公开(公告)日：2022-04-14

申请号：US17069741

申请日：2020-10-13

Applicant: Maplebear, Inc. (dba Instacart)

Inventor： Abhay Pawar

IPC: G06Q30/06 ,  G06Q30/02 ,  G06N20/00

Abstract: An online concierge system maintains a graph of items available for purchase. The graph maintains edges between items, where an edge between an item and an additional item indicates that one or more customers have previously replaced the item with the additional item. The edge between the item and the additional item also identifies a number of times customers have replaced the item with the additional item. When a customer orders an item, the online concierge system traverses the graph of items to identify candidate replacement items for the ordered item and identifies one or more of the candidate replacement items to the customer. When identifying the candidate replacement items, the online concierge system accounts for distance between the ordered item and different candidate replacement items in the item graph.

公开(公告)号：US12131358B1

公开(公告)日：2024-10-29

申请号：US16816226

申请日：2020-03-11

Applicant: Maplebear, Inc.

Inventor： Sharath Rao Karikurve ,  Abhay Pawar ,  Shishir Kumar Prasad

IPC: G06Q30/0601 ,  G06N20/00 ,  G06Q10/0875 ,  G06Q20/40 ,  G06Q30/0204 ,  G06N7/01

CPC classification number: G06Q30/0605 ,  G06N20/00 ,  G06Q10/0875 ,  G06Q20/407 ,  G06Q30/0205 ,  G06Q30/0623 ,  G06Q30/0631 ,  G06Q30/0635 ,  G06Q30/0639 ,  G06N7/01

Abstract: In an online concierge system, a shopper retrieves items specified in an order by a customer from a retail location. The online concierge system optimizes order fulfillment by selecting a retail location for an order that is most time-efficient and that is most likely to have each of the item in the order available. Hence, the online concierge system may select a less convenient retail location that is more likely to have each item being ordered available. To predict whether a retail location incompletely fulfill the order if selected to fulfill the order, the online concierge system trains a machine learning model based on prior orders fulfilled by the retail location, a shopper retrieving items in the order, items in the order, and other features.

公开(公告)号：US20240020748A1

公开(公告)日：2024-01-18

申请号：US18473978

申请日：2023-09-25

Applicant: Maplebear Inc.

Inventor： Abhay Pawar

IPC: G06Q30/0601 ,  G06N20/00 ,  G06Q30/0282

CPC classification number: G06Q30/0631 ,  G06Q30/0637 ,  G06N20/00 ,  G06Q30/0282 ,  G06Q50/28

Abstract: An online concierge system maintains a graph of items available for purchase. The graph maintains edges between items, where an edge between an item and an additional item indicates that one or more customers have previously replaced the item with the additional item. The edge between the item and the additional item also identifies a number of times customers have replaced the item with the additional item. When a customer orders an item, the online concierge system traverses the graph of items to identify candidate replacement items for the ordered item and identifies one or more of the candidate replacement items to the customer. When identifying the candidate replacement items, the online concierge system accounts for distance between the ordered item and different candidate replacement items in the item graph.

公开(公告)号：US20250022024A1

公开(公告)日：2025-01-16

申请号：US18898272

申请日：2024-09-26

Applicant: Maplebear Inc.

Inventor： Sharath Rao Karikurve ,  Abhay Pawar ,  Shishir Kumar Prasad

IPC: G06Q30/0601 ,  G06N7/01 ,  G06N20/00 ,  G06Q10/0875 ,  G06Q20/40 ,  G06Q30/0204

Abstract: A system or a method for fulfilling orders using a machine-learned model in an online system. When a user places an order, the system accesses a model trained on historical data, including characteristics of candidate locations, previous orders, and recent inventory records. The model predicts the probability that each candidate location will incompletely fulfill the order. The system selects the location with the lowest probability of incomplete fulfillment and sends fulfillment instructions to client devices of available shoppers. After the order is fulfilled, the system receives data from the client devices of shoppers, identifies whether the order was completely fulfilled, and updates the machine-learned model based on the actual outcomes.

公开(公告)号：US11803891B2

公开(公告)日：2023-10-31

申请号：US17069741

申请日：2020-10-13

Applicant: Maplebear, Inc.

Inventor： Abhay Pawar

IPC: G06Q30/06 ,  G06Q30/02 ,  G06N20/20 ,  G06Q30/0601 ,  G06N20/00 ,  G06Q30/0282 ,  G06Q50/00 ,  G06Q50/28

CPC classification number: G06Q30/0631 ,  G06N20/00 ,  G06Q30/0282 ,  G06Q30/0637 ,  G06Q50/28

Abstract: An online concierge system maintains a graph of items available for purchase. The graph maintains edges between items, where an edge between an item and an additional item indicates that one or more customers have previously replaced the item with the additional item. The edge between the item and the additional item also identifies a number of times customers have replaced the item with the additional item. When a customer orders an item, the online concierge system traverses the graph of items to identify candidate replacement items for the ordered item and identifies one or more of the candidate replacement items to the customer. When identifying the candidate replacement items, the online concierge system accounts for distance between the ordered item and different candidate replacement items in the item graph.

公开(公告)号：US20220292567A1

公开(公告)日：2022-09-15

申请号：US17196855

申请日：2021-03-09

Applicant: Maplebear, Inc. (dba Instacart)

Inventor： Shishir Kumar Prasad ,  Sharath Rao Karikurve ,  Abhay Pawar

IPC: G06Q30/06 ,  G06Q10/08 ,  G06F16/28 ,  G06F16/2457 ,  G06N20/00

Abstract: An online concierge system accesses a hierarchical taxonomy of products each labeled with a category of the hierarchical taxonomy. The online concierge system receives, from an inventory database, an unlabeled product, which not included in the hierarchical taxonomy. The online concierge system inputs the unlabeled product to a replacement model. The replacement model is trained to output, for each of one or more labeled products from the hierarchical taxonomy, a likelihood that a user would select the labeled product as a replacement for an input product. The online concierge system selects a labeled product from the one or more labeled products based on the likelihoods. The online concierge system adds the unlabeled product to a category of the hierarchical taxonomy based on the selected labeled product.