公开(公告)号：US20240331015A1

公开(公告)日：2024-10-03

申请号：US18129464

申请日：2023-03-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Kenneth Jason Sanchez ,  Eric Hermann

IPC: G06Q30/0601 ,  G06Q30/02

CPC classification number: G06Q30/0635 ,  G06Q30/0281 ,  G06Q30/0639

Abstract: An online concierge system facilitates creation of shopping lists of items for ordering from a physical retail store and at least partial self-service fulfillment of orders by the customer. To support fulfillment by the customer, the online concierge system may intelligently select one or more items of the order to be picked by a third-party picker and prepopulated to a shopping cart reserved for the customer in advance of the customer arriving at the retail location. The items for prepopulating may be selected based on various factors that optimize prepopulation decisions on an item-by-item basis in accordance with various machine learning models. The online concierge system may furthermore facilitate procurement of the remaining items by the customer through a customer client device that may track item procurement and/or provide guidance for locating items.

公开(公告)号：US20240330977A1

公开(公告)日：2024-10-03

申请号：US18129447

申请日：2023-03-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Cheng Jia ,  Justin Miller ,  Yan Zhuang ,  Anvar Gazizov ,  Hassan Djirdeh ,  Aakarsh Madhavan ,  Brijendra Nag ,  Ji Chao Zhang

IPC: G06Q30/0242 ,  G06Q30/0273

CPC classification number: G06Q30/0243 ,  G06Q30/0275

Abstract: A keyword campaign automatically groups keywords for customized override bids for the keyword group. The keywords of a campaign may be analyzed by a computer model to predict membership in a category in addition to the likelihood that the bid of the keyword will be modified. The keyword groups may be automatically generated based on the predictions, and performance metrics are evaluated for the keyword groups at one or more modified bids. The performance metrics of the keyword groups at the modified bids may then be used to set override bids. The automatically generated keyword groups and performance metrics permit a sponsor to intelligently group and customize keyword bids with reduced interface interactions and without requiring individual keyword bid adjustments.

公开(公告)号：US20240249335A1

公开(公告)日：2024-07-25

申请号：US18159357

申请日：2023-01-25

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Taesik Na ,  Vinesh Reddy Gudla ,  Xiao Xiao

IPC: G06Q30/0601 ,  G06F16/9535 ,  G06Q30/0201

CPC classification number: G06Q30/0631 ,  G06F16/9535 ,  G06Q30/0201

Abstract: An online system displays search results in response to a query by receiving a query from a customer. An online system accesses a set of candidate items and computes a relevance score and personalization score for each item. The online system computes the relevance score based on query data and item data and may normalize the relevance score. The online system computes the personalization score based on item data, such as an item embedding, and user data, such as a user embedding. The online system computes a query specificity score and adjusts the personalization score with the query specificity score such that generic queries have high personalization scores and specific queries have low personalization scores. The online system combines the relevance and personalization scores for each candidate item into a ranking score and displays the candidate items to the customer based on their ranking scores.

公开(公告)号：US20240242145A1

公开(公告)日：2024-07-18

申请号：US18156347

申请日：2023-01-18

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Haochen Luo ,  Eric Hermann ,  Rishab Saraf ,  Abhinav Darbari ,  Teodor Lefter ,  Jason Sanchez ,  Jagannath Putrevu

IPC: G06Q10/0631 ,  G06Q10/0639 ,  G06Q10/0835 ,  G06Q10/087 ,  G06Q30/0202 ,  G06Q30/0601

CPC classification number: G06Q10/063118 ,  G06Q10/06398 ,  G06Q10/08355 ,  G06Q10/087 ,  G06Q30/0202 ,  G06Q30/0635

Abstract: An online concierge shopping system fulfills orders using workers who pick items at a warehouse to complete an order and workers to deliver the orders to a customer's location. To optimize the staffing of workers for each task, the system uses a trained model to predict the number of workers needed to achieve an optimal outcome based on an input set of contextual information. The system also schedules specific workers to various shifts using the predicted number of workers needed and then searching a feasibility space for an optimal solution. The trained model may be updated based on performance observations.

公开(公告)号：US20240202694A1

公开(公告)日：2024-06-20

申请号：US18169012

申请日：2023-02-14

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Ganglu Wu ,  Shiyuan Yang ,  Xiao Zhou ,  Qi Wang ,  Qunwei Liu ,  Youming Luo

IPC: G06Q20/20 ,  G06K7/14 ,  G06Q30/0601 ,  G06T3/40 ,  G06V10/25

CPC classification number: G06Q20/208 ,  G06K7/1443 ,  G06Q30/0633 ,  G06Q30/0641 ,  G06T3/40 ,  G06V10/25

Abstract: An automated checkout system modifies received images of machine-readable labels to improve the performance of a label detection model that the system uses to decode item identifiers encoded in the machine-readable labels. For example, the automated checkout system may transform subregions of an image of a machine-readable label to adjust for distortions in the image's depiction of the machine-readable label. Similarly, the automated checkout system may identify readable regions within received images of machine-readable labels and apply a label detection model to those readable regions. By modifying received images of machine-readable labels, these techniques improve on existing computer-vision technologies by allowing for the effective decoding of machine-readable labels based on real-world images using relatively clean training data.

公开(公告)号：US20240177226A1

公开(公告)日：2024-05-30

申请号：US18072487

申请日：2022-11-30

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Andrew Peters ,  Dominic Cocchiarella ,  Brandon Leonardo ,  David McIntosh ,  Varouj Chitilian

IPC: G06Q30/0601 ,  G06Q30/0207 ,  G06Q30/0251 ,  G06T13/40 ,  H04W4/021

CPC classification number: G06Q30/0643 ,  G06Q30/0209 ,  G06Q30/0255 ,  G06Q30/0261 ,  G06Q30/0271 ,  G06Q30/0631 ,  G06T13/40 ,  H04W4/021

Abstract: A computing platform may receive, from a user device, historical shopping information indicating previously purchased items and/or previous routes within shopping environments for a first user of the user device. The computing platform may input, into a shopping gamification model, the historical shopping information, which may output shopping recommendation information indicating one or more of: recommended items or recommended routes within a first shopping environment. The computing platform may send, to the user device, a shopping gamification interface that includes the shopping recommendation information and one or more commands directing the user device to display the shopping gamification interface. The computing platform may receive, from the user device, user feedback information indicating acceptance or rejection of the shopping recommendation information by the first user. The computing platform may update, based on the user feedback information, the shopping gamification model.

公开(公告)号：US20240104569A1

公开(公告)日：2024-03-28

申请号：US17955228

申请日：2022-09-28

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Rohit Turumella ,  Yehonatah Afek ,  Chun-Che Wang ,  Leslie McFadden ,  Thomas Doan

IPC: G06Q20/40 ,  G06Q30/06

CPC classification number: G06Q20/4016 ,  G06Q30/0617 ,  G06Q30/0635

Abstract: An online concierge system facilitates a checkout bypass process for shoppers. The online concierge system detects when the shopper procuring an order for a customer is ready to exit the warehouse after obtaining the items in the order. The online concierge system applies a trained risk model to automatically determining whether to initiate an audit of the shopper. Responsive to determining to initiate the audit, the online concierge system invokes an auditing process. The online concierge system receives, via an auditor application, verification of the order from the auditor mobile application. Responsive to the verification, the online concierge system completes the order and generates routing instructions via the shopper mobile application for facilitating delivery by the shopper to the customer.

公开(公告)号：US20240104493A1

公开(公告)日：2024-03-28

申请号：US17935091

申请日：2022-09-24

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Reza Faturechi ,  Dylan Wang ,  Brian Duggan ,  Xianlei Qiu ,  Atul Gupte ,  Bing Hong Leonard How

IPC: G06Q10/08 ,  G06Q10/06

CPC classification number: G06Q10/087 ,  G06Q10/06312 ,  G06Q10/0639

Abstract: An online concierge system generates order batches for pickers and offers those order batches. The online concierge system generates a set of candidate order batches, which are subsets of a received set of orders. The online concierge system generates a set of order batch scores for each of a set of candidate pickers, and offers the candidate order batches to the candidate pickers for the candidate pickers to service based on the set of order batch scores. If a candidate picker accepts the offered order batch, the online concierge system identifies candidate order batches with overlapping orders with the order batch accepted by the candidate picker, and rescinds the offer for each of the candidate pickers to service the order batches.

公开(公告)号：US20240070746A1

公开(公告)日：2024-02-29

申请号：US17899483

申请日：2022-08-30

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Girija Narlikar ,  Sharath Rao Karikurve

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

CPC classification number: G06Q30/0631 ,  G06N20/00 ,  G06Q30/0201 ,  G06Q30/0633

Abstract: A method implemented at a computer system includes, responsive to identifying an opportunity to present content to a target user, accessing a machine learning model trained on a dataset containing input features of a plurality of users and labels indicating openness metrics of the respective plurality of users. The machine learning model is then applied to a set of features of the target user to output an openness metric that predicts a loss in the target user's response rate when contextual relevance is not considered in selection of recommendation for the target user. A recommendation is then selected from a plurality of candidate recommendations based on the openness metric and sent for display to the target user.

公开(公告)号：US20240070393A1

公开(公告)日：2024-02-29

申请号：US17821889

申请日：2022-08-24

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Shishir Kumar Prasad ,  Cameron Nicholas Taylor ,  John Salaveria ,  Joey Loi ,  Kevin McCullough

IPC: G06F40/284 ,  G06Q30/06

CPC classification number: G06F40/284 ,  G06Q30/0621

Abstract: An online concierge system generates suggested instructions for presentation to a user. The online concierge system access instruction examples corresponding to a target item category and generates candidate instruction representations based on instruction messages within each instruction example. The online concierge system generates preliminary scores for the candidate instruction representations that are directly related to an intra-category frequency of use of the instruction tokens of the candidate instruction representation within the target item category. The online system normalizes these preliminary scores for the candidate instruction representations based on the inter-category frequency of use of the instruction tokens in all item categories to generate final scores for the candidate instruction representations. The online concierge system selects a set of instruction representations based on these final scores and generates suggested instructions based on the set of instruction representations.