公开(公告)号：US12175482B2

公开(公告)日：2024-12-24

申请号：US17486395

申请日：2021-09-27

Applicant: Maplebear Inc.

Inventor： Tejaswi Tenneti ,  Tyler Russell Tate ,  Jonathan Lennart Bender ,  Shishir Kumar Prasad ,  Qingyuan Chen

IPC: G06Q10/00 ,  G06F16/901 ,  G06F16/9535 ,  G06Q30/0201 ,  G06Q30/0601

Abstract: An online concierge system suggests subsequent search queries based on previous search queries and whether the previous search queries resulted in conversions. The online concierge system trains a machine learning model using previous delivery orders and whether initial and subsequent search queries in the previous delivery orders resulted in conversions. 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 items related to the search query. In response to the search query resulting in a conversion, the online concierge system retrieves a conversion graph and presents a suggested subsequent search query based on the conversion graph. In response to the search query not resulting in a conversion, the online concierge system retrieves a non-conversion graph and presents a suggested subsequent search query based on the non-conversion graph.

公开(公告)号：US20240303711A1

公开(公告)日：2024-09-12

申请号：US18596592

申请日：2024-03-05

Applicant: Maplebear Inc.

Inventor： Li Tan ,  Tejaswi Tenneti ,  Shishir Kumar Prasad ,  Huapu Pan ,  Allan Stewart ,  Taesik Na ,  Tyler Russell Tate ,  Joshua Roberts ,  Haixun Wang

IPC: G06Q30/0601 ,  G06F16/9532

CPC classification number: G06Q30/0627 ,  G06F16/9532 ,  G06Q30/0635

Abstract: A system, for example, an online system uses a machine learning based language model, for example, a large language model (LLM) to process high-level natural language queries received from users. The system receives a natural language query from a user of a client device. The system determines contextual information associated with the query. Based on this information, the system generates a prompt for the machine learning based language model. The system receives a response from the machine learning based language model. The system uses the response to generate a search query for a database. The system obtains results returned by the database in response to the search query and provides them to the user. The system allows users to specify high level natural language queries to obtain relevant search results, thereby improving the overall user experience.

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：US20230394551A1

公开(公告)日：2023-12-07

申请号：US18236371

申请日：2023-08-21

Applicant: Maplebear, Inc.

Inventor： Tyler Russell Tate ,  Jason Scott ,  Logan William Murdock ,  Tejaswi Tenneti

IPC: G06Q30/0601 ,  G06F16/9538 ,  G06Q30/0283 ,  G06Q10/087

CPC classification number: G06Q30/0631 ,  G06Q30/0635 ,  G06F16/9538 ,  G06Q30/0603 ,  G06Q30/0283 ,  G06Q30/0641 ,  G06Q10/087 ,  G06Q30/0625 ,  G06Q30/0617

Abstract: An online system provides options for selection by a user. The online system receives a query entered on a client device. The online system queries an item database to retrieve a set of items related to the query and assigns each item to a product category in a predefined taxonomy that maps items to product categories. The online system inputs each item into a prediction model trained to predict a probability that an item is available at a warehouse location. The online system determines that a first product category has low availability based on predicted probabilities for items in the first product category. Responsive to determining that a first product category has low availability, the online system generates a generic item for the first product category and sends a list of items including the generic item to the client device for display responsive to the query.

公开(公告)号：US20230260007A1

公开(公告)日：2023-08-17

申请号：US18139289

申请日：2023-04-25

Applicant: Maplebear Inc. (dba Instacart)

Inventor： William Silverthorne Faurot, III ,  Tyler Russell Tate

IPC: G06Q30/0601 ,  G06F16/2457 ,  G06N20/00

CPC classification number: G06Q30/0631 ,  G06Q30/0641 ,  G06F16/24578 ,  G06N20/00

Abstract: An online system receives a recipe from a customer mobile device. The online system performs natural language processing on the recipe to determine parsed ingredients. For each of one or more of the determined parsed ingredients, the online system maps the parsed ingredient to a generic item. The online system queries a product database with the mapped generic item to obtain one or more products associated with the mapped generic item. The online system applies a machine-learned conversion model to each of the one or more products to determine a conversion likelihood for the product. The conversion model may be trained based on historical data describing previous conversions made by customers presented with an opportunity to add products to an order. The online system selects a product from the one or more products based on the determined conversion likelihoods and adds the selected product to an order.

公开(公告)号：US11710171B2

公开(公告)日：2023-07-25

申请号：US17682444

申请日：2022-02-28

Applicant: Maplebear Inc.

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

IPC: G06Q30/00 ,  G06Q30/0601

CPC classification number: G06Q30/0631 ,  G06Q30/0627 ,  G06Q30/0629 ,  G06Q30/0633 ,  G06Q30/0639

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：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：US20250078101A1

公开(公告)日：2025-03-06

申请号：US18954374

申请日：2024-11-20

Applicant: Maplebear Inc.

Inventor： Tejaswi Tenneti ,  Tyler Russell Tate ,  Jonathan Lennart Bender ,  Shishir Kumar Prasad ,  Qingyuan Chen

IPC: G06Q30/0201 ,  G06F16/901 ,  G06F16/9535 ,  G06Q30/0601

Abstract: An online concierge system suggests subsequent search queries based on previous search queries and whether the previous search queries resulted in conversions. The online concierge system trains a machine learning model using previous delivery orders and whether initial and subsequent search queries in the previous delivery orders resulted in conversions. 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 items related to the search query. In response to the search query resulting in a conversion, the online concierge system retrieves a conversion graph and presents a suggested subsequent search query based on the conversion graph. In response to the search query not resulting in a conversion, the online concierge system retrieves a non-conversion graph and presents a suggested subsequent search query based on the non-conversion graph.

公开(公告)号：US20240161163A1

公开(公告)日：2024-05-16

申请号：US18420594

申请日：2024-01-23

Applicant: Maplebear Inc.

Inventor： Jonathan Lennart Bender ,  Tyler Russell Tate ,  Tejaswi Tenneti ,  Aditya Subramanian

IPC: G06Q30/0601 ,  G06F16/901 ,  G06F17/18

CPC classification number: G06Q30/0625 ,  G06F16/9024 ,  G06F17/18

Abstract: An online concierge system generates an item graph connecting item nodes with attribute nodes of the items. 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 may determine that no item nodes meet presentation criteria. The online concierge system may determine that a reformulated search query has a higher conversion probability than the search query received from the customer. The online concierge system reformulates the search query. The online concierge system selects item nodes as search results. The online concierge system transmits the search results to the customer.

公开(公告)号：US11915289B2

公开(公告)日：2024-02-27

申请号：US17188214

申请日：2021-03-01

Applicant: Maplebear, Inc.

Inventor： Jonathan Lennart Bender ,  Tyler Russell Tate ,  Tejaswi Tenneti ,  Aditya Subramanian

IPC: G06Q30/00 ,  G06Q30/0601 ,  G06F16/901 ,  G06F17/18

CPC classification number: G06Q30/0625 ,  G06F16/9024 ,  G06F17/18

Abstract: An online concierge system generates an item graph connecting item nodes with attribute nodes of the items. 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 may determine that no item nodes meet presentation criteria. The online concierge system may determine that a reformulated search query has a higher conversion probability than the search query received from the customer. The online concierge system reformulates the search query. The online concierge system selects item nodes as search results. The online concierge system transmits the search results to the customer.