公开(公告)号：US20250005650A1

公开(公告)日：2025-01-02

申请号：US18217337

申请日：2023-06-30

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Muhammad Iftekher Chowdhury

IPC: G06Q30/0601 ,  H04L51/046 ,  H04W12/033

Abstract: An online concierge system provides a client application executed on a client device for customers to generate orders for fulfillment by the online concierge system. If the client device is unable to establish a data connection to a network, the client application locally caches data on the client device for one or more retailers that includes items that have been previously purchased by the customer or that are popular among customers. The customer generates an order through the client application for a retailer based on the locally cached items for the retailer. The online concierge system application generates an encrypted text message based on the order that is transmitted to the online concierge system via short message service (SMS). The online concierge system may also return messages via SMS, which may be presented by the client application.

公开(公告)号：US20250005279A1

公开(公告)日：2025-01-02

申请号：US18215505

申请日：2023-06-28

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Shih-Ting Lin ,  Prithvishankar Srinivasan ,  Saurav Manchanda ,  Shishir Kumar Prasad ,  Min Xie

IPC: G06F40/247 ,  G06F16/21 ,  G06F16/215 ,  G06F16/28

Abstract: A computer system uses clustering and a large language model (LLM) to normalize attribute tuples for items stored in a database of an online system. The online system collects attribute tuples, each attribute tuple comprising an attribute type and an attribute value for an item. The online system initially clusters the attribute tuples into a first plurality of clusters. The online system generates prompts for input into the LLM, each prompt including a subset of attribute tuples grouped into a respective cluster of the first plurality. Based on the prompts, the LLM generates a second plurality of clusters, each cluster including one or more attribute tuples that have a common attribute type and a common attribute value. The online system maps each attribute tuple to a respective normalized attribute tuple associated with each cluster. The online system rewrites each attribute tuple in the database to a corresponding normalized attribute tuple.

公开(公告)号：US20240428304A1

公开(公告)日：2024-12-26

申请号：US18212633

申请日：2023-06-21

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Christopher Hans Nietes Rudnick ,  Imaan Munir ,  Eduardo Martin Alarcon Villaran ,  Miranda Bouck ,  Uladzimir Bahatyrevich

IPC: G06Q30/0601

Abstract: A scrollable listing of icons associated with catalogs is displayed, in which the scrollable listing of icons is overlaid onto a page and remains fixed when the page is scrolled, each icon is associated with a catalog, and each icon is displayed with an indication of a set of items selected from a corresponding catalog. In response to a user selection of an icon from the scrollable listing of icons, the page is updated to include items included in a catalog associated with the selected icon. In response to a user selection to add an item from the page including the items, the indication displayed with the selected icon in the scrollable listing of icons is updated to indicate the added item.

公开(公告)号：US20240420209A1

公开(公告)日：2024-12-19

申请号：US18209178

申请日：2023-06-13

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Amalia Rothschild-Keita

IPC: G06Q30/0601

Abstract: Automatic creation of lists of items at an online system organized around co-occurrences of items. The online system provides inputs into a computer model, the inputs including information about items purchased by a user of the online system over a defined time period, information about a catalog of items stored at one or more computer-readable media of the online system, and a plurality of recipes each including a set of co-occurring items. The online system applies the computer model to generate an indication of co-occurrence of each pair of items in each recipe. The online system generates one or more lists of items based on the indication of co-occurrence, each of the one or more lists of items associated with a respective recipe. The online system causes a device of the user to display a user interface with the one or more lists of items for presentation to the user.

公开(公告)号：US20240394771A1

公开(公告)日：2024-11-28

申请号：US18202768

申请日：2023-05-26

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Shrikar Archak ,  Shishir Kumar Prasad

IPC: G06Q30/0601 ,  G06Q30/08

Abstract: Embodiments relate to automatically generating a basket of items to be recommended to a user of an online system. The online system communicates a basket opportunity to a group of retailers, wherein the basket opportunity defines a plurality of item categories each associated with a respective item to be included in a basket. The online system receives, from each retailer in response to the basket opportunity, a respective bid of a plurality of bids for the basket opportunity. The online system applies a computer model to each bid to determine a score for each bid and selects a winning bid for the user based on determined scores for the bids. For each item category, the online system populates the basket with a respective item from a catalog of a retailer that is associated with the winning bid. The online system then presents the basket with items to the user.

公开(公告)号：US20240394093A1

公开(公告)日：2024-11-28

申请号：US18324783

申请日：2023-05-26

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Siddarth Kalra ,  Gareth Pennington ,  Sumiran Pradhan ,  Levon Dolbakian ,  Eric Guffey

IPC: G06F9/48 ,  G06F9/448

Abstract: An online system predicts a number of interruption events within a time period and identifies anomalous numbers of interruption events using an interruption prediction model. The online concierge system maintains application state data that describes a state of an application workflow for a client application. The online concierge system identifies interruption events that represent interruptions to the application workflow and logs interruption events in an interruption log, wherein each entry of the interruption log describes an interruption event and its corresponding state. The online concierge system predicts a number of interruption events that will occur within a time period based on an interruption prediction model. The online concierge system computes an actual number of interruption events that occurred during the time period and computes a difference between the actual number and the predicted number. If the difference exceeds a threshold value, the online concierge system performs a remedial action.

公开(公告)号：US20240378637A1

公开(公告)日：2024-11-14

申请号：US18196395

申请日：2023-05-11

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Vijay Sivasubramaniam ,  Hang Li ,  Yingshi Zhang ,  Senduren Sivakumar

IPC: G06Q30/0242 ,  G06Q30/0241 ,  G06Q30/0251

Abstract: An online system receives, from an entity, a content item to be presented to online system users, in which the content item includes a landing page to a third-party website. The system accesses the landing page, identifies a set of items included in it, and determines whether the landing page is configured for performing one or more types of conversions associated with each item. The system matches one or more of the items with one or more target objects based on the determination and associates the matched target object(s) with the content item. The system receives information describing one or more impression events associated with presenting the content item to a user and information describing a conversion associated with a target object associated with the content item performed by the user, applies an attribution model to determine a contribution of the impression event(s) to the conversion, and reports the contribution.

公开(公告)号：US20240362581A1

公开(公告)日：2024-10-31

申请号：US18141397

申请日：2023-04-29

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Vladimir Katz ,  Ajay Pankaj Sampat ,  Fangzhou Wang ,  Wenqi Ge ,  Charles Durham ,  Kevin Shepherd

IPC: G06Q10/087 ,  G06N7/01 ,  G06N20/00

CPC classification number: G06Q10/087 ,  G06N7/01 ,  G06N20/00

Abstract: An online concierge system allows users to place orders for fulfillment by pickers. Orders have various attributes (e.g., dimensions, weight, contents, etc.), and the pickers may have corresponding characteristics affecting capability of fulfilling orders. To optimize allocation of orders to pickers for fulfillment, the online concierge system trains an order validation model that predicts a probability of a picker encountering a problem fulfilling an order based on characteristics of the picker and attributes of the order. The order validation model is trained from training examples based on previous orders and labels indicating whether a picker encountered a problem with fulfilling the order. The order validation model can then be used to predict deliverability of future orders or to specify limits on one or more attributes of orders for fulfillment.

公开(公告)号：US20240362579A1

公开(公告)日：2024-10-31

申请号：US18141393

申请日：2023-04-29

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Haochen Luo ,  Kenneth Jason Sanchez ,  Eric Hermann

IPC: G06Q10/087

CPC classification number: G06Q10/087

Abstract: An inventory interaction model predicts user interactions with items of a location for a physical warehouse included with other warehouses in a region. The location is described with features that include the nearby locations and the respective user interactions with the respective item assortments, so that the item interactions for the evaluated location incorporate location-location effects in model predictions. To effectively train the model in the absence of prior interaction data for a location, training examples are generated from existing locations and user interaction data of item assortments by selecting a portion of the locations for the training examples and including nearby location interaction data, labeling the training example output with item interactions for the location. The trained model is then applied for an item assortment at a location by describing nearby locations in evaluating candidate locations and item assortments.

公开(公告)号：US20240354812A1

公开(公告)日：2024-10-24

申请号：US18137389

申请日：2023-04-20

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Ming Li ,  Natalie Binns ,  Dmytro Solomadin ,  Zhiyi Fan

IPC: G06Q30/0241

CPC classification number: G06Q30/0276

Abstract: An online system receives information identifying items associated with a brand, a hierarchical taxonomy of the items, and information identifying a retailer associated with the brand. The system applies a machine learning model to predict availabilities of the items at (a) retailer location(s) associated with the retailer, identifies items that are likely available at the retailer location(s), and groups the identified items into categories based on the taxonomy. The system computes an item score for each item based on its popularity, attributes, and/or attributes of a user. The system assigns items in each category to positions within a display unit associated with the category and computes a category score for each category based on the item scores. The system assigns display units associated with the categories to positions within a template based on the category score and generates a page associated with the brand and retailer based on the assignments.