公开(公告)号：US20230080205A1

公开(公告)日：2023-03-16

申请号：US17476475

申请日：2021-09-16

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Manmeet Singh ,  Tejaswi Tenneti ,  Will Faurot, III ,  Tyler Tate ,  Toni Chau ,  Sathya Hariesh Prakash

IPC: G06Q10/08 ,  G06Q10/04 ,  G06K9/62 ,  G06F16/9535

Abstract: An online concierge system suggests recipes to users to encourage them to include items from the recipes in orders. When suggesting a recipe to a user, the online concierge system maps generic item descriptions in a recipe to specific items for sale at a warehouse identified by the user. The online concierge system maintains a recipe store including mappings of generic item descriptions in recipes to specific items. To determine mappings between generic item descriptions and specific items, the online concierge system determines a category from a taxonomy for a generic item description in a recipe and excludes specific items in different categories than the determined category. As recipes are displayed to users, the online concierge system may receive inputs from users that are used to modify mappings between generic item descriptions and specific items

公开(公告)号：US20220358562A1

公开(公告)日：2022-11-10

申请号：US17682444

申请日：2022-02-28

Applicant: Maplebear Inc.(dba Instacart)

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

IPC: G06Q30/06

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.

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.

公开(公告)号：US20230117762A1

公开(公告)日：2023-04-20

申请号：US17503245

申请日：2021-10-15

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Manmeet Singh ,  Tejaswi Tenneti

IPC: G06Q30/06 ,  G06N3/02

Abstract: An online concierge system improves on methods for presenting content to users. The online concierge system generates a user embedding for a user and recipe embeddings for candidate recipes. The online concierge system generates a context embedding by applying a context embedding model to context data received from a user mobile application. The online concierge system calculates an overall score for each candidate recipe based on a user score and a context score. The user score is calculated based on the user embedding and a recipe embedding for the candidate recipe. The context score is calculated based on the generated context embedding and the recipe embedding for the candidate recipe. The online system selects a recipe for presentation to the user based on the overall scores. The online concierge system trains the context embedding model using a loss function that is based on the user score and the context score.

公开(公告)号：US20230273940A1

公开(公告)日：2023-08-31

申请号：US17682187

申请日：2022-02-28

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Guanghua Shu ,  Taesik Na ,  Zhihong Xu ,  Wideet Shende ,  Manmeet Singh ,  Tejaswi Tenneti ,  Reza Sadri

IPC: G06F16/28 ,  G06F16/22 ,  G06F16/2455 ,  G06F11/34

CPC classification number: G06F16/283 ,  G06F16/2228 ,  G06F16/24556 ,  G06F16/285 ,  G06F11/3409

Abstract: An online system maintains item embeddings for items. As a number of items maintained by the online system increases, maintaining a single index of the item embeddings is increasingly difficult. To increase scalability, the online system partitions item embeddings into multiple indices, with each index corresponding to a value of a specific attribute maintained by the online system for items. For example, an online system generates indices that each correspond to a different warehouse offering items. To expedite retrieval of item embeddings, the online system allocates each index to one of a number of shards. When the online system receives a query, the online system determines an embedding for the query and retrieves an index from a shard based on metadata received with the query. Based on distances between the query for the embedding and the item embeddings in the retrieved index, the online system selects one or more items.

公开(公告)号：US20230289868A1

公开(公告)日：2023-09-14

申请号：US17871790

申请日：2022-07-22

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Jonathan Lennart Bender ,  Kevin Lau ,  Silas Burton ,  Prakash Putta ,  Manmeet Singh ,  Tejaswi Tenneti

IPC: G06Q30/06 ,  G06F16/9538 ,  G06F16/906 ,  G06N5/02

CPC classification number: G06Q30/0643 ,  G06F16/9538 ,  G06F16/906 ,  G06N5/022 ,  G06F3/0482

Abstract: An online concierge system receives a search query from a client device. The online concierge system identifies a set of matching items from an item database. The matching items correspond to the received search query. The online concierge system obtains, from a hierarchical item taxonomy, a category label for each matching item. The item taxonomy relates each item in the item database to one of a plurality of category labels. The online concierge system groups the matching items by the category labels for each of the matching items into one or more groups. The online concierge system generates instructions for a user interface. The user interface includes a scrollable list of one or more carousels. Each carousel includes a scrollable list of a group of the one or more groups. The online concierge system sends the instructions of the user interface to the client device for display.