公开(公告)号：US20240104622A1

公开(公告)日：2024-03-28

申请号：US17955250

申请日：2022-09-28

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Vinesh Reddy Gudla ,  Tyler Russell Tate ,  Tejaswi Tenneti ,  Akshay Nair

IPC: G06Q30/06 ,  G06Q30/02

CPC classification number: G06Q30/0629 ,  G06Q30/0201 ,  G06Q30/0204

Abstract: An online system receives a search query from a client device associated with a user and queries a database including item data for a set of items matching the query, in which the set of items is at a retailer location associated with a retailer type and each item is associated with an item category. For each item of the set, a machine learning model is applied to predict a probability of conversion for the user and item and a score is computed based on an expected value, in which the expected value is based on a value associated with the item and the probability. The score for each item is boosted based on the item category, retailer type, or a user segment that is based on the user's historical order data. The items are ranked based on the boosted scores and the ranking is sent to the client device.

公开(公告)号：US20240070747A1

公开(公告)日：2024-02-29

申请号：US17900744

申请日：2022-08-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Joey Loi ,  Eugene Agronin ,  Viswa Mani Kiran Peddinti

IPC: G06Q30/06 ,  G06Q10/08 ,  G06Q30/02

CPC classification number: G06Q30/0631 ,  G06Q10/087 ,  G06Q30/0208 ,  G06Q30/0281

Abstract: An item availability model produces item verification notifications, for example, by receiving data indicating a plurality of items associated with an online shopping concierge platform; determining based at least in part on the data indicating the plurality of items and one or more machine learning (ML) models, a subset of the plurality of items for which to have one or more shoppers associated with the online shopping concierge platform check current availability at one or more warehouse locations associated with the online shopping concierge platform; and generating and transmitting communications comprising at least one of dispatching, instructing, incentivizing, or encouraging the one or more shoppers to check the current availability of at least a portion of the subset of the plurality of items at the one or more warehouse locations.

公开(公告)号：US20240046313A1

公开(公告)日：2024-02-08

申请号：US17877748

申请日：2022-07-29

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Luis Manrique ,  Aamir Poonawalla ,  Amin Akbari ,  Shesh Nath Mishra ,  Eitan Pinhas Teruzzi Katznelson

IPC: G06Q30/02 ,  G06Q10/08 ,  G06Q30/08

CPC classification number: G06Q30/0272 ,  G06Q10/087 ,  G06Q30/08

Abstract: An online concierge system facilitates procurement and delivery of items for customers using a network of shoppers. The online concierge system includes a promotion management engine that paces delivery of promotions for content campaigns based in part on predicted item availability and a paced spending model that operates to pace spending of a content campaign over a budget period. The system paces the delivery by determining whether to enter a bid for the impression opportunity by comparing an observed cumulative spend for the content campaign during a portion of the budget period prior to the impression time and a desired cumulative spend for the content campaign during the portion of the budget period prior to the impression time based on the distribution of impression opportunities and a budget for the content campaign during the budget period.

公开(公告)号：US20240037863A1

公开(公告)日：2024-02-01

申请号：US17877676

申请日：2022-07-29

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Dominic Cocchiarella ,  Aditya Godbole ,  Andrew Peters ,  Spencer Schack ,  Brandon Leonardo

IPC: G06T19/00 ,  G06Q30/06

CPC classification number: G06T19/006 ,  G06Q30/0643 ,  G06Q30/0627 ,  G06Q30/0629 ,  G06Q30/0631

Abstract: An augmented reality application executing on a client device receives video data captured by a camera of the device, in which the video data includes a display area of the device. The application detects a set of items within the display area based on the video data, wherein the set of items is included among an inventory of a warehouse associated with a retailer, and accesses a set of attributes of each item. The application retrieves profile information including a set of preferences associated with a customer of the retailer, matches one or more of the set of preferences with one or more attributes of each item, and generates an augmented reality element based on the matches. The augmented reality element is then displayed, such that it is overlaid onto a portion of the display area based on a location within the display area at which the items are detected.

公开(公告)号：US20240029132A1

公开(公告)日：2024-01-25

申请号：US17868572

申请日：2022-07-19

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Shih-Ting Lin ,  Amirali Darvishzadeh ,  Min Xie ,  Haixun Wang

IPC: G06Q30/06 ,  G06F40/20

CPC classification number: G06Q30/0627 ,  G06F40/20 ,  G06N20/00

Abstract: To improve attribute prediction for items, item categories are associated with a schema that is augmented with additional attributes and/or attribute labels. Items may be organized into categories and similar categories may be related to one another, for example in a taxonomy or other organizational structure. An attribute extraction model may be trained for each category based on an initial attribute schema for the respective category and the items of that category. The extraction model trained for one category may be used to identify additional attributes and/or attribute labels for the same or another, related category.

公开(公告)号：US20230385911A1

公开(公告)日：2023-11-30

申请号：US17752061

申请日：2022-05-24

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Danna Weintraub ,  Erik Wolfe

IPC: G06Q30/06

CPC classification number: G06Q30/0639 ,  G06Q30/0643 ,  G06Q30/0633

Abstract: An online system may receive, from a user device, a request to view, at a graphical user interface, available entries of a third-party system. The third-party system may operate multiple physical locations. The operation of each physical location is documented by a time-sensitive dataset which includes multiple dynamic item entries. The online system may retrieve a geographical location associated with the user device and determine a subset of physical locations operated by the third-party system that are eligible for further selection based on distances of the physical locations from the geographical location associated with the user device. The online system may determine a metric measuring a size of the dynamic item entries available in the time-sensitive dataset and select one of the physical locations based on the metric. The online system may cause for display the dynamic item entries in the time-sensitive dataset associated with the selected physical location.

公开(公告)号：US20230351319A1

公开(公告)日：2023-11-02

申请号：US17733267

申请日：2022-04-29

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Xianlei Qiu ,  Site Wang ,  Deepak Tirumalasetty

IPC: G06Q10/08 ,  G06Q30/02

CPC classification number: G06Q10/087 ,  G06Q30/0283

Abstract: An online concierge system receives information describing orders from its customers and generates a route for each order based on this information. The routes are partitioned into multiple sets of routes and multiple candidate generation processes are executed in parallel. During execution of a candidate generation process, one or more routes included in each set of routes are paired with shoppers of the system based on a set of constraints, producing multiple route-shopper pairs. A cost associated with each route-shopper pair is determined based on attributes associated with each shopper and/or information associated with each route of the pair. During an optimization process, which is executed asynchronously with the candidate generation process, one or more route-shopper pairs are selected based on pairing-cost data identifying route-shopper pairs and their associated costs. One or more requests to fulfill orders are sent to one or more shoppers based on the selected route-shopper pair(s).

公开(公告)号：US20230325856A1

公开(公告)日：2023-10-12

申请号：US18186141

申请日：2023-03-17

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Trace Levinson ,  Nicholas Sturm

IPC: G06Q30/0202

CPC classification number: G06Q30/0202

Abstract: An online system computes an incremental cost prediction for each of a set of user-treatment pairs to select a set of treatments to apply to users to satisfy a predicted interaction gap. The online system generates a set of candidate user-treatment pairs that each include user data for a user of the online system and treatment data for a treatment of a set of treatments. The online system computes an incremental interaction prediction and a treatment cost prediction for each of the candidate user-treatment pairs by applying an incremental interaction model to the user data and the treatment data in each user-treatment pair. The online system computes incremental cost predictions for each of the user-treatment pairs based on the computed incremental interaction predictions and treatment cost predictions and selects which users to apply treatments to and which treatments to apply to those users based on the incremental cost predictions.

公开(公告)号：US20230316375A1

公开(公告)日：2023-10-05

申请号：US17709998

申请日：2022-03-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Ramasubramanian Balasubramanian ,  Girija Narlikar ,  Omar Alonso

IPC: G06Q30/06 ,  G06N3/08

CPC classification number: G06Q30/0631 ,  G06N3/08

Abstract: An online concierge system generates recipe embeddings for recipes including multiple items and user embeddings for users, with the recipe embeddings and user embeddings in a common latent space. To generate the user embeddings and the recipe embeddings, a model includes separate layers for a user model outputting user embeddings and for a recipe model outputting recipe embeddings. When training the model, a weight matrix generates a predicted dietary preference type for a user embedding and for a recipe embedding and adjusts the user model or the recipe model based on differences between the predicted dietary preference type and a dietary preference type applied to the user embedding and to the recipe embedding. Additionally cross-modal layers generate a predicted user embedding from a recipe embedding and generate a predicted recipe embedding from a user embedding that are used to further refine the user model and the recipe model.

公开(公告)号：US20230260007A1

公开(公告)日：2023-08-17

申请号：US18139289

申请日：2023-04-25

Applicant: Maplebear Inc. (dba Instacart)

Inventor： William Silverthorne Faurot, III ,  Tyler Russell Tate

IPC: G06Q30/0601 ,  G06F16/2457 ,  G06N20/00

CPC classification number: G06Q30/0631 ,  G06Q30/0641 ,  G06F16/24578 ,  G06N20/00

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.