公开(公告)号：US20230139335A1

公开(公告)日：2023-05-04

申请号：US18090506

申请日：2022-12-29

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Shishir Kumar Prasad ,  Sharath Rao Karikurve

IPC: G06Q30/0601 ,  G06F16/953

Abstract: An online concierge system may determine recommended search terms for a user. The online concierge system may receive a request from a user to view a user interface configured to receive a search query. The online concierge system retrieves long-term activity data including previous search terms entered by the user while searching for items to add to an online shopping cart. For each previous search term, the online concierge system retrieves categorical search terms corresponding to one or more categories to which the previous search term was mapped. The online concierge system determines a set of nearby categorical search terms and sends, for display via a client device, the set of nearby categorical search terms as recommended search terms.

公开(公告)号：US20230056148A1

公开(公告)日：2023-02-23

申请号：US17406027

申请日：2021-08-18

Applicant: Maplebear Inc.(dba Instacart)

Inventor： Negin Entezari ,  Sharath Rao Karikurve ,  Shishir Kumar Prasad ,  Haixun Wang

IPC: G06Q30/06 ,  G06Q10/08

Abstract: An online concierge shopping system identifies candidate items to a user for inclusion in an order based on prior user inclusion of items in orders and items currently included in the order. From a multi-dimensional tensor generated from cooccurrences of items in orders from various users, the online concierge system generates item embeddings and user embeddings in a common latent space by decomposing the multi-dimensional tensor. From items included in an order, the online concierge system generates an order embedding from item embeddings of the items included in the order. Scores for candidate items are determined based on similarity of item embeddings for the candidate items to the order embedding. Candidate items are selected based on their scores, with the selected candidate items identified to the user.

公开(公告)号：US20250095055A1

公开(公告)日：2025-03-20

申请号：US18965960

申请日：2024-12-02

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Jeffrey Bernard Arnold ,  Rob Donnelly ,  Sumit Garg ,  Jonathan Gu ,  Bill Lundberg ,  David Pal ,  Sharath Rao Karikurve ,  Peng Qi

IPC: G06Q30/0601 ,  G06F9/451 ,  G06Q30/02

Abstract: An online concierge system includes sponsored content items in an interface including different slots for displaying content items. A sponsored content item may be displayed in a single slot or in multiple adjacent slots. The online concierge system determines a content score for various sponsored content items indicating a likelihood of a user interacting with a sponsored content item and a position bias for slots in the interface indicating a likelihood of the user interacting with a slot independent of content in the slot. Position biases are different dependent on a number of slots in which a content item is displayed. The online concierge system generates a graph identifying potential placements of sponsored content items in slots by selecting content items in an order according to their content scores. Sponsored content items are positioned in slots according to a path through the graph that has the highest overall expected value.

公开(公告)号：US20240330846A1

公开(公告)日：2024-10-03

申请号：US18129021

申请日：2023-03-30

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Sharath Rao Karikurve ,  Ramasubramanian Balasubramanian ,  Ashish Sinha

IPC: G06Q10/0835 ,  G06Q10/087 ,  G06Q30/0203

CPC classification number: G06Q10/08355 ,  G06Q10/087 ,  G06Q30/0203 ,  G06N20/00

Abstract: An online concierge system receives, from a client device associated with a user of the online concierge system, order data associated with an order placed with the online concierge system, in which the order data describes a delivery location for the order. The online concierge system receives information describing a set of attributes associated with the delivery location and accesses a machine learning model trained to predict a difference between an arrival time and a delivery time for the delivery location. The online concierge system applies the model to the set of attributes associated with the delivery location to predict the difference between the arrival time and the delivery time for the delivery location and determines an estimated delivery time for the order based at least in part on the predicted difference. The online concierge system sends the estimated delivery time for the order for display to the client device.

公开(公告)号：US20240289855A1

公开(公告)日：2024-08-29

申请号：US18113965

申请日：2023-02-24

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Ramasubramanian Balasubramanian ,  Sharath Rao Karikurve

IPC: G06Q30/0601 ,  G06N3/08

CPC classification number: G06Q30/0613 ,  G06N3/08

Abstract: A specific item is identified to suggest a replacement therefor to a user. A set of candidate replacement items for the specific item is determined. For at least one of the candidate replacement items, an expiration score is determined based on expiration information associated with the item. A replacement score for the candidate replacement item is determined by inputting the determined expiration score as a feature into a machine learning model that is trained using features of historical samples of candidate replacement items suggested as a replacement to users and the replacement suggestion being accepted by the users. One or more of the candidate replacement items is selected based on respective replacement scores as one or more suggested replacement items. A graphical user interface of a client device of the user is caused to display the one or more suggested replacement items as the replacement for the specific item.

公开(公告)号：US20230316381A1

公开(公告)日：2023-10-05

申请号：US18207632

申请日：2023-06-08

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Manmeet Singh ,  Tyler Russell Tate ,  Tejaswi Tenneti ,  Sharath Rao Karikurve

IPC: G06Q30/0601

CPC classification number: G06Q30/0631 ,  G06Q30/0627 ,  G06Q30/0633 ,  G06Q30/0639 ,  G06Q30/0629

Abstract: An online concierge shopping system identifies recipes to users to encourage them to include items from the recipes in orders. The online concierge system maintains user embeddings for users and recipe embeddings for recipes. For users who have not placed orders, recipes are recommended based on global user interactions with recipes. Users who have previously ordered items from recipes are suggested recipes selected based on a similarity of their user embedding to recipe embeddings. Users who have purchased items but not from recipes are compared to a set of similar users based on the user embeddings, and recipes with which users of the set of similar users interacted are used for identifying recipes to the users. A recipe graph may be maintained by the online concierge system to identify similarities between recipes for expanding candidate recipes to suggest to users.