公开(公告)号：US20240354825A1

公开(公告)日：2024-10-24

申请号：US18138657

申请日：2023-04-24

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Vinesh Reddy Gudla ,  Prakash Putta ,  Tejaswi Tenneti ,  Prathyusha Bhaskar Karnam

IPC: G06Q30/0601 ,  G06Q10/083 ,  G06Q10/087

CPC classification number: G06Q30/0625 ,  G06Q10/083 ,  G06Q10/087 ,  G06Q30/0635

Abstract: A search module for an online concierge system executes searches in response to a search query with respect to item databases of retailers. The search module dynamically configures a recall set size that controls a number of search results returned for a search query based in part on a query entropy representing an estimated breadth of the search term. The query entropy may be determined relative to a diversity of items in a retailer's database. The recall set size may be configured relative to the query entropy in a manner that manages a tradeoff between latency of search execution and search result quality.

公开(公告)号：US20240330718A1

公开(公告)日：2024-10-03

申请号：US18625042

申请日：2024-04-02

Applicant: Maplebear Inc.

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

IPC: G06N5/022 ,  G06F16/901 ,  G06F40/205 ,  G06F40/40

CPC classification number: G06N5/022 ,  G06F16/9024 ,  G06F40/205 ,  G06F40/40

Abstract: An online system generates a knowledge graph database representing relationships between entities in the online system. The online system generates the knowledge graph database by at least obtaining descriptions for an item. The online system generates one or more prompts to a machine-learned language model, where a prompt includes a request to extract a set of attributes for the item from the description of the item. The online system receives a response generated from executing the machine-learned language model on the prompts. The online system parses the response to extract the set of attributes for the item. For each extracted attribute, the online system generates connections between an item node representing the item and a set of attribute nodes for the extracted set of attributes in the database.

公开(公告)号：US20230252032A1

公开(公告)日：2023-08-10

申请号：US17666531

申请日：2022-02-07

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Taesik Na ,  Zhihong Xu ,  Guanghua Shu ,  Tejaswi Tenneti ,  Haixun Wang

IPC: G06F16/2457 ,  G06F16/242

CPC classification number: G06F16/24578 ,  G06F16/2438

Abstract: An online system maintains various items and maintains values for different attributes of the items, as well as an item embedding for each item. When the online system receives a query for retrieving one or more items, the online system generates an embedding for the query. Based on measures of similarity between the embedding for the query and item embeddings, the online system selects a set of items. The online system identifies a specific attribute of items and generates a whitelist of values for the specific attribute based on measures of similarity between item embeddings for items in the selected set and the embedding for the query. The online system removes items having values for the selected attribute outside of the whitelist of values from the selected set of items to identify items more likely to be relevant to the query.

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：US20220414746A1

公开(公告)日：2022-12-29

申请号：US17929797

申请日：2022-09-06

Applicant: Maplebear, Inc. (dba Instacart)

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

IPC: G06Q30/06 ,  G06F16/9538 ,  G06Q30/02 ,  G06Q10/08

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：US20220277373A1

公开(公告)日：2022-09-01

申请号：US17188214

申请日：2021-03-01

Applicant: Maplebear, Inc. (dba Instacart)

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

IPC: G06Q30/06 ,  G06F17/18 ,  G06F16/901

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：US20250156926A1

公开(公告)日：2025-05-15

申请号：US18943691

申请日：2024-11-11

Applicant: Maplebear Inc.

Inventor： Haixun Wang ,  Shrikar Archak ,  Tejaswi Tenneti

IPC: G06Q30/0601 ,  G06F16/9535 ,  G06F16/955 ,  G06Q30/08

Abstract: An online system receives a user request from a client device through the interface, identifies one or more featured products based on the query, and generates a prompt for input to a machine-learned generative language model. The prompt specifies both the user's request and a request to suggest the featured products in association with a response to the user request. This prompt is fed into a machine-learned language model via a model serving system for execution. The online system receives a response generated by the model, generates a query response based on the response generated by the model, and transmits instructions to the client device to display the query response. The online system collects data on user interactions with the uses the collected data to fine-tune the machine-learned generative language model.

公开(公告)号：US20250005654A1

公开(公告)日：2025-01-02

申请号：US18217329

申请日：2023-06-30

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Raochuan Fan ,  Prakash Putta ,  Vinesh Reddy Gudla ,  Nkemakonam Paulet Okoye ,  Taesik Na ,  Tejaswi Tenneti

IPC: G06Q30/0601

Abstract: An online concierge system allows a customer to search items offered by a retailer by providing a set of items to the customer based on a search query. To account for varying availability of items at the retailer, the online concierge system modifies rankings in the set of items having less than a threshold predicted availability at the retailer. This reduces a likelihood selection of an item likely to be unavailable at the retailer. To maintain customer confidence in the items selected based on the search results by maintaining visibility of items relevant to the search query, the online concierge system determines how much an item is modified within the set based on search query attributes, item attributes, or customer characteristics. This allows different items to be adjusted different amounts in a set based on the item, as well as the search query for which the item was selected.

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.