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公开(公告)号:US20230146336A1
公开(公告)日:2023-05-11
申请号:US17524491
申请日:2021-11-11
Applicant: Maplebear Inc. (dba Instacart)
Inventor: Haixun Wang , Taesik Na , Tejaswi Tenneti , Saurav Manchanda , Min Xie , Chuan Lei
CPC classification number: G06Q30/0603 , G06N20/00
Abstract: To simplify retrieval of items from a database that at least partially satisfy a received query, an online concierge system trains a model that outputs scores for items from the database without initially retrieving items for evaluation by the model. The online concierge system pre-trains the model using natural language inputs corresponding to items from the database, with a natural language input including masked words that the model is trained to predict. Subsequently, the model is refined using multi-task training where a task is trained to predict scores for items from the received query. The online concierge system selects items for display in response to the received query based on the predicted scores.
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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.
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公开(公告)号:US20240289867A1
公开(公告)日:2024-08-29
申请号:US18113870
申请日:2023-02-24
Applicant: Maplebear Inc. (dba Instacart)
Inventor: Xuan Zhang , Vinesh Reddy Gudla , Tejaswi Tenneti , Haixun Wang
IPC: G06Q30/0601
CPC classification number: G06Q30/0633 , G06Q30/0619 , G06Q30/0631
Abstract: An online system generates a template shopping list for a user by accessing a machine learning model trained based on historical order information associated with the user, applying the model to predict likelihoods of conversion for item categories by the user, and populating the template shopping list with one or more item categories based on the predicted likelihoods. The system ranks one or more item types associated with each item category in the template shopping list and determines a set of collection rules associated with one or more item categories/types based on the historical order information. The system generates a suggested shopping list by populating each item category in the template shopping list with one or more item types and a quantity of each item type based on the ranking and rules and sends the suggested shopping list and rules for display to a client device associated with the user.
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公开(公告)号:US20240177212A1
公开(公告)日:2024-05-30
申请号:US18072353
申请日:2022-11-30
Applicant: Maplebear Inc. (dba Instacart)
Inventor: Aditya Subramanian , Prakash Putta , Tejaswi Tenneti , Jonathan Lennart Bender , Xiao Xiao , Taesik Na
IPC: G06Q30/0601
CPC classification number: G06Q30/0631
Abstract: To determine search results for an online shopping concierge platform, the platform may receive, from a computing device associated with a customer of an online shopping concierge platform, data describing one or more search parameters input by the customer; identify, based at least in part on the data describing the search parameter(s), products offered by the online shopping concierge platform that are at least in part responsive to the search parameter(s); and determine, for each product and based at least in part on one or more machine learning (ML) models, a relevance of the product to one or more taxonomy levels of a product catalog associated with the online shopping concierge platform, a likelihood that the customer would be offended by inclusion of the product amongst displayed responsive search results, and/or the like.
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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.
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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.
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公开(公告)号:US20230222162A1
公开(公告)日:2023-07-13
申请号:US18185091
申请日:2023-03-16
Applicant: Maplebear Inc. (dba Instacart)
Inventor: Jonathan Lennart Bender , Tyler Russell Tate , Tejaswi Tenneti , Qingyuan Chen
IPC: G06Q30/0201 , G06Q30/0601
CPC classification number: G06Q30/0201 , G06Q30/0641 , G06Q30/0635
Abstract: An online concierge system generates an item graph connecting item nodes with attribute nodes of the items. Example attributes include a brand, a category, a department, or any other suitable information about the item. When the online concierge system receives a search query to identify one or more items from a customer, the online concierge system parses the search query into combinations of terms and identifies item nodes and attribute nodes related to the search query. The online concierge system identifies item nodes and attribute nodes that are likely to result in a conversion. Information about the identified nodes is presented to the customer. The customer may select an item node to purchase the item, or an attribute node to execute a new search query based on terms associated with the attribute node.
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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
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.
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公开(公告)号:US20230086846A1
公开(公告)日:2023-03-23
申请号:US17478411
申请日:2021-09-17
Applicant: Maplebear Inc. (dba Instacart)
Inventor: Tejaswi Tenneti , Esther Vasiete , Nitin Pasari
IPC: G06Q30/06 , G06F16/2457 , G06F16/9535 , G06F16/9538 , G06N3/08
Abstract: An online concierge system displays a search interface to users. The search interface receives s prefix of a search query from a user and determines terms for completing the prefix, with the terms displayed to a user as suggestions via the search interface. The online concierge system determines probabilities of the user adding items corresponding to terms for completing the prefix when different terms are displayed. The online concierge system displays the terms for completing the prefix in an order based on the determined probabilities of including a corresponding item in an order rather than in an order based on likelihoods of the user selecting different terms.
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公开(公告)号:US20220237679A1
公开(公告)日:2022-07-28
申请号:US17160759
申请日:2021-01-28
Applicant: Maplebear, Inc.(dba Instacart)
Inventor: Tejaswi Tenneti , Aditya Subramanian , Shrikar Archak , Tyler Russell Tate , Jonathan Lennart Bender
IPC: G06Q30/06 , G06F16/901 , G06F16/2457 , G06F16/248
Abstract: An online concierge system generates a graph connecting items with attributes of the items and other items. Hence, the graph includes nodes corresponding to attributes and nodes corresponding to items, with an item connected to attributes of the item in the graph. Example attributes include a brand, a category, a department, or any other suitable information about the item. When the online concierge system receives a search query to identify one or more items from a customer, the online concierge system parses the search query into combinations of terms and compares different combinations of terms to the graph to determine connections between different combinations of terms in the graph. Based on measures of connectedness between combinations of terms and connections in the graph, items are identified from one or more combinations of terms. Information about the identified items is presented to the customer.
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