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公开(公告)号:US20220335489A1
公开(公告)日:2022-10-20
申请号:US17232621
申请日:2021-04-16
Applicant: Maplebear, Inc.(dba Instacart)
Inventor: Sharath Rao Karikurve , Angadh Singh
Abstract: An online concierge system maintains information about items offered for purchase and users of the online concierge system. Based on prior purchases of items by users, the online concierge system trains a model to determine a likelihood of a user purchasing an item based on an embedding for the object and embedding for the user. The online concierge system identifies a collection of items and generates an embedding for the collection. The collection may be a cluster of items determined from similarities between embeddings of items. Alternatively, the collection may be a group of items having a common category. The online concierge system includes one or more collections of items along with individual items when recommending items for the users, so the trained model is applied to embeddings of the individual items and to embeddings of the one or more collections to generate recommendations for a user.
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公开(公告)号:US20220292568A1
公开(公告)日:2022-09-15
申请号:US17196879
申请日:2021-03-09
Applicant: Maplebear, Inc. (dba Instacart)
Inventor: William Silverthorne Faurot, III , Tyler Russell Tate
IPC: G06Q30/06 , G06N20/00 , G06F16/2457
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.
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公开(公告)号:US20220261744A1
公开(公告)日:2022-08-18
申请号:US17178183
申请日:2021-02-17
Applicant: Maplebear, Inc. (DBA Instacart)
Inventor: Anastasija Kovalova , Neera Chatterjee
Abstract: An online system receives, from a customer mobile application (CMA) an order including a high-value item determines that the order includes the high-value item. The online system transmits an indication that the order includes the high-value item to a delivery mobile application (DMA). The DMA transmits a real-time location of a client device of a delivery agent to the online system. Responsive to determining that the delivery agent is at a delivery location, the online system transmits an indication to the DMA to display a user interface including an interactive element for requesting a signature from a customer. Responsive to receiving an indication of an interaction with the interactive element, the online system transmits an indication to the CMA to display a user interface with a signature element. The CMA transmits a signature received via the signature element to the online system, which stores the signature as verification information.
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公开(公告)号:US20220114640A1
公开(公告)日:2022-04-14
申请号:US17069741
申请日:2020-10-13
Applicant: Maplebear, Inc. (dba Instacart)
Inventor: Abhay Pawar
Abstract: An online concierge system maintains a graph of items available for purchase. The graph maintains edges between items, where an edge between an item and an additional item indicates that one or more customers have previously replaced the item with the additional item. The edge between the item and the additional item also identifies a number of times customers have replaced the item with the additional item. When a customer orders an item, the online concierge system traverses the graph of items to identify candidate replacement items for the ordered item and identifies one or more of the candidate replacement items to the customer. When identifying the candidate replacement items, the online concierge system accounts for distance between the ordered item and different candidate replacement items in the item graph.
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公开(公告)号:US20210233319A1
公开(公告)日:2021-07-29
申请号:US17227346
申请日:2021-04-11
Applicant: Maplebear, Inc. (dba Instacart)
Inventor: Carlos H. Cardonha , Fernando L. Koch , James R. Kraemer
IPC: G06T19/00 , G06F16/29 , G06F16/2455 , G06F16/583 , G06F16/58 , G06F16/9537 , G06F16/955 , G06K9/52 , G06K9/62 , G09G5/00
Abstract: A method for tag-based search includes capturing an image, extracting a tag from the image, identifying a location associated with the captured image, and querying stored content for information that matches the location and the tag. Local storage is checked for the information first, and remote storage may be checked subsequently. Any located information may be used to augment the image. Information located in the remote storage may be saved in the local storage until it reaches a certain age, until it fails to be accessed for a threshold period of time, or until the location moves outside a threshold radius associated with a location of the information located in the remote storage.
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公开(公告)号:US20210133665A1
公开(公告)日:2021-05-06
申请号:US16670447
申请日:2019-10-31
Applicant: Maplebear, Inc. (dba Instacart)
Inventor: Daniel Hsiao , Jason Scott , Michael Jablonski , Nima Zahedi
Abstract: An online concierge system receives an order from a customer. The online concierge system transmits a notification to the customer's client device indicating that the order is ready for pick up and receives location data from the customer's client device as the customer travels to a pickup location. In response to the online concierge system receiving a first indication that the customer has entered an outer geofence, the online concierge system transmits a second notification to a runner's client device that the customer is in transit. In response to the online concierge system receiving a second indication that the customer has entered an inner geofence, the online concierge system starts a timer. When the online system receives a confirmation that the order has been picked up by the customer, it stops the timer and computes a wait time for pick up of the order.
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公开(公告)号:US20250095044A1
公开(公告)日:2025-03-20
申请号:US18965973
申请日:2024-12-02
Applicant: Maplebear Inc. (dba Instacart)
Inventor: Shishir Kumar Prasad , Sharath Rao Karikurve
IPC: G06Q30/0601 , G06F16/953
Abstract: An online concierge system may determine recommended search terms for a user. The online concierge system may receive a request from a user to view a user interface configured to receive a search query. The online concierge system retrieves long-term activity data including previous search terms entered by the user while searching for items to add to an online shopping cart. For each previous search term, the online concierge system retrieves categorical search terms corresponding to one or more categories to which the previous search term was mapped. The online concierge system determines a set of nearby categorical search terms and sends, for display via a client device, the set of nearby categorical search terms as recommended search terms.
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48.
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.
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公开(公告)号:US20250005381A1
公开(公告)日:2025-01-02
申请号:US18217356
申请日:2023-06-30
Applicant: Maplebear Inc. (dba Instacart)
Inventor: Peng Qi , Cheng Jia , Xiyu Wang , Qiao Jiang , Sharad Gupta , David Pal , Joseph Haraldson , Zhenbang Chen
IPC: G06N5/022
Abstract: An online system manages presentation of content items in various presentation contexts such as when the users are browsing pages or when the users have entered a search query. The online system trains a single unified machine learning model that predicts one or more likelihoods of a target event associated with presentation of a content item in the different presentation contexts. The learned model is applied to a set of candidate content items associated with a presentation opportunity in a specific context. Features that are inapplicable to the specific context may be masked when applying the model. The online system may select between the candidate content items based on the predicted likelihoods using the model trained across the multiple different contexts, such that the prediction for one context may be based in part on learned outcomes in other related contexts.
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50.
公开(公告)号:US20240428315A1
公开(公告)日:2024-12-26
申请号:US18213764
申请日:2023-06-23
Applicant: Maplebear Inc. (dba Instacart)
Inventor: Sharath Rao Karikurve , Ramasubramanian Balasubramanian
IPC: G06Q30/0601
Abstract: An online system provides a platform for users to place orders at different physical retailers. When a user moves from one location to another (e.g., the user physically moves or is traveling), where the user's preferred retailer is not available, the online system suggests a new retailer for the user and optionally items to purchase at the new retailer. When a user accesses the online system from a new location, the system obtains the user's previous purchases and computes a repurchase probability. The system then ranks candidate new retailers in the new location based on their match to the likely repurchased items. To suggest new items to buy at the new retailer, the system uses existing replacement models to suggest replacements for the items that the user is likely to buy based on previous purchases.
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