公开(公告)号：US20240135423A1

公开(公告)日：2024-04-25

申请号：US18047990

申请日：2022-10-18

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Shitao Wang ,  Apurvaa Subramaniam ,  Nicholas George Gordenier

IPC: G06Q30/06

CPC classification number: G06Q30/0631

Abstract: An online concierge system generates an aggregated lift score for a test feature for the online concierge system. The online concierge presents prioritized items from a set of item groups to two sets of users: a test set and a control set. The online concierge system uses the test feature to present prioritized items to users in the test set, and the online concierge system uses existing functionality to present prioritized items to users in the control set. For each test group, the online concierge system creates holdout subsets out of the test set and the control set. The online concierge system tracks user interactions with items in an item group and computes a group lift score for the item group. The online concierge system generates an aggregated lift score for the test feature based on the group lift scores and presents items to users based on the aggregated lift score.

公开(公告)号：US20240112238A1

公开(公告)日：2024-04-04

申请号：US17956217

申请日：2022-09-29

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Girija Narlikar ,  Karuna Ahuja ,  Radhika Goel ,  Chakshu Ahuja ,  Xiaoming Zhang ,  Devlina Das

IPC: G06Q30/06 ,  G06Q30/02 ,  G06Q30/08 ,  G06Q50/00

CPC classification number: G06Q30/0631 ,  G06Q30/0203 ,  G06Q30/0603 ,  G06Q30/08 ,  G06Q50/01

Abstract: An online concierge system receives a request to purchase a gift for a user of the system and retrieves a profile associated with the user. Based on the profile and attributes of items included among inventories of one or more retailer locations, the system identifies a set of candidate items for which the user is likely to have an affinity. The system accesses a machine learning model trained to predict a giftability score for an item and applies the model to attributes of each candidate item to predict its giftability score. Based on its giftability score and the profile, the system computes a composite score for each candidate item indicating an appropriateness of gifting the candidate item to the user. The system ranks the set of candidate items based on the composite scores and selects one or more suggested items for gifting to the user based on the ranking.

公开(公告)号：US11947632B2

公开(公告)日：2024-04-02

申请号：US17405011

申请日：2021-08-17

Applicant: Maplebear Inc.

Inventor： Saurav Manchanda ,  Krishnakumar Subramanian ,  Haixun Wang ,  Min Xie

IPC: G06F18/2411 ,  G06F18/214 ,  G06F18/22 ,  G06N3/084

CPC classification number: G06F18/2411 ,  G06F18/214 ,  G06F18/22 ,  G06N3/084

Abstract: An online concierge system trains a classification model as a domain adversarial neural network from training data labeled with source classes from a source domain that do not overlap with target classes from a target domain output by the classification model. The online concierge system maps one or more source classes to a target class. The classification model extracts features from an image, classifies whether an image is from the source domain or the target domain, and predicts a target class for an image from the extracted features. The classification model includes a gradient reversal layer between feature extraction layers and the domain classifier that is used during training, so the feature extraction layers extract domain invariant features from an image.

公开(公告)号：US11947617B2

公开(公告)日：2024-04-02

申请号：US18205949

申请日：2023-06-05

Applicant: Maplebear Inc.

Inventor： Ogden Kent ,  Benjamin David Bader ,  Jeffrey Bernard Arnold

IPC: G06F16/958 ,  G06F11/34 ,  G06F16/957 ,  G06F40/143

CPC classification number: G06F16/9577 ,  G06F11/3476 ,  G06F16/958 ,  G06F40/143

Abstract: A variation testing system environment for performing variation testing of web pages and applications is disclosed. The variation testing system applies a weighted consistent hash function to user attributes of users to assign the users to a variant of a web page that is undergoing experimentation. The usage of the weighted consistent hash function allows for a stable experimental population.

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：US11935109B2

公开(公告)日：2024-03-19

申请号：US17709998

申请日：2022-03-31

Applicant: Maplebear Inc.

Inventor： Ramasubramanian Balasubramanian ,  Girija Narlikar ,  Omar Alonso

IPC: G06Q30/0601 ,  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：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：US20240062273A1

公开(公告)日：2024-02-22

申请号：US18499609

申请日：2023-11-01

Applicant: Maplebear Inc.

Inventor： Camille van Horne ,  Philip Goolkasian

IPC: G06Q30/0601 ,  G06F3/0482 ,  H04L51/046

CPC classification number: G06Q30/0635 ,  G06F3/0482 ,  G06Q30/0641 ,  H04L51/046 ,  G06F3/0485

Abstract: In a delivery service, a picker retrieves items specified in an order by a customer. If a picker encounters an issue with an item in the order, the picker may select, via a user interface, the item and an associated template message, which requests input from the customer regarding a course of action for the item, to send to the customer. The customer may select, via another user interface, a template message describing a course of action for the item. In response to receiving one of a subset of template messages, the online concierge system displays via the user interface, a set of replacement options to the customer, who may select one of the replacement options to be sent to the picker with the template message.

公开(公告)号：US11908290B2

公开(公告)日：2024-02-20

申请号：US17323031

申请日：2021-05-18

Applicant: Maplebear Inc.

Inventor： Lin Gao ,  Shiyuan Yang

IPC: G07G1/14 ,  A47F9/04 ,  G01G19/415 ,  G01G21/22 ,  G06Q20/20 ,  G07G1/00 ,  G06V20/40 ,  G06V20/52 ,  G06V20/68

CPC classification number: G07G1/14 ,  A47F9/048 ,  G01G19/415 ,  G01G21/22 ,  G06Q20/208 ,  G06V20/44 ,  G07G1/0072 ,  G06V20/52 ,  G06V20/68

Abstract: Disclosed are visual recognition and sensor fusion weight detection system and method. An example method includes: tracking, by a sensor system, objects and motions within a selected area of a store; activating, by the sensor system, a first computing device positioned in the selected area in response to detecting a presence of a customer within the selected area; identifying, by the sensor system, the customer and at least one item carried by the customer; transmitting, by the sensor system, identifying information of the customer and the at least one item to a computing server system via a communication network; measuring, by the first computing device, a weight of the at least one item; transmitting, by the first computing device, the weight to the computing server system via the communication network; and generating, by the computing server system, via the communication network, transaction information of the at least one item.

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.