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公开(公告)号：US20240362678A1
公开(公告)日：2024-10-31
申请号：US18141396
申请日：2023-04-29
发明人： Chakshu Ahuja , Girija Narlikar , Karuna Ahuja
IPC分类号： G06Q30/0251 , G06N20/00
CPC分类号： G06Q30/0261 , G06N20/00
摘要： For each retailer location associated with multiple retailers, an online system associated with the retailers receives video data captured within the retailer location by a camera of a client device associated with an online system user. The online system detects, based at least in part on the video data, a location associated with the user within the retailer location and/or an interaction by the user with an item included among an inventory of the retailer location. The online system generates a set of signals associated with the user based at least in part on the detection of the location and/or the interaction. Based at least in part on the set of signals, the online system determines a set of preferences associated with the user, trains a machine learning model to predict a metric associated with the user, and/or sends content for display to a client device associated with the user.
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公开(公告)号：US20240193657A1
公开(公告)日：2024-06-13
申请号：US18079544
申请日：2022-12-12
发明人： Sneha Chandrababu , Karuna Ahuja
IPC分类号： G06Q30/0601
CPC分类号： G06Q30/0617 , G06Q30/0633
摘要： An online concierge system generates an order including multiple items based on unstructured data received from a user through a chat interface instead of manually adding items to the order. The user provides unstructured data to the online concierge system through the chat interface, and the online concierge system extracts an intent from the unstructured data using a natural language process. Based on the intent, the online concierge system identifies a group of items associated with the intent and selects a group of items. The online concierge system generates an order for the user that includes the items comprising the selected group of items.
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公开(公告)号：US20240144172A1
公开(公告)日：2024-05-02
申请号：US17977724
申请日：2022-10-31
发明人： Apurvaa Subramanian , Girija Narlikar , Chakshu Ahuja , Karuna Ahuja , Radhika Goel , Sneha Chandrababu
CPC分类号： G06Q10/087 , G06Q10/083 , G06Q30/0206 , G06Q30/0635
摘要： An online concierge system facilitates a concierge service for ordering, procurement, and delivery of food items from physical retailers. The order fulfillment is based in part on automatically inferring one or more quality metrics, such as remaining shelf-life, associated with perishable food items. A picker shopping on behalf of a customer may capture images of available food items for the order using a picker client device. The images are processed through a machine learning model to infer the one or more quality metrics, and a price is then determined based in part on a dynamic pricing model. The online concierge system communicates with a customer client device to meet quality characteristics and pricing preferences set by the customer. The online concierge system may further facilitate a checkout process for the items obtained by the picker and may facilitate delivery of the items by the picker to the customer.
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公开(公告)号：US20240112238A1
公开(公告)日：2024-04-04
申请号：US17956217
申请日：2022-09-29
发明人： Girija Narlikar , Karuna Ahuja , Radhika Goel , Chakshu Ahuja , Xiaoming Zhang , Devlina Das
CPC分类号： G06Q30/0631 , G06Q30/0203 , G06Q30/0603 , G06Q30/08 , G06Q50/01
摘要： An online concierge system receives a request to purchase a gift for a user of the system and retrieves a profile associated with the user. Based on the profile and attributes of items included among inventories of one or more retailer locations, the system identifies a set of candidate items for which the user is likely to have an affinity. The system accesses a machine learning model trained to predict a giftability score for an item and applies the model to attributes of each candidate item to predict its giftability score. Based on its giftability score and the profile, the system computes a composite score for each candidate item indicating an appropriateness of gifting the candidate item to the user. The system ranks the set of candidate items based on the composite scores and selects one or more suggested items for gifting to the user based on the ranking.
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5.发明公开公开(公告)号：US20240289873A1
公开(公告)日：2024-08-29
申请号：US18113562
申请日：2023-02-23
IPC分类号： G06Q30/08 , G06N20/00 , G06Q30/0601
CPC分类号： G06Q30/08 , G06N20/00 , G06Q30/0613
摘要： An online system manages campaign participation by a plurality of sub-campaigns with a reinforcement learning model. The reinforcement learning model determines a current context and determines an action that affects the participation of the individual sub-campaigns. The reinforcement learning model may thus dynamically control the participation over time as different objectives are achieved by the sub-campaigns and may account for the different contexts that change over time.
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6.发明公开公开(公告)号：US20240144173A1
公开(公告)日：2024-05-02
申请号：US17977734
申请日：2022-10-31
发明人： Karuna Ahuja , Girija Narlikar , Sneha Chandrababu , Gowri Rajeev , Lan Wang , Chakshu Ahuja , Sonal Jain
CPC分类号： G06Q10/087 , G06K7/10366 , G06K7/1417 , G06Q30/0202 , G06Q30/0623
摘要： An online concierge system detects acquired items included among an inventory of a customer and identifies one or more candidate available items from the acquired items based on a predicted perishability of each item and a predicted amount of each item that was used. The system retrieves recipes, matches the item(s) likely to be available to a set of recipes based on their ingredients, and identifies any remaining items for each matched recipe not likely to be available. The system retrieves a set of attributes associated with the customer and the set of recipes and computes a suggestion score for each recipe based on the attributes. The system ranks the recipes based on their scores, identifies one or more recipes for suggesting to the customer based on the ranking, and sends the recipe(s) and any remaining items for each recipe to a client device associated with the customer.
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公开(公告)号：US20240070210A1
公开(公告)日：2024-02-29
申请号：US17899441
申请日：2022-08-30
IPC分类号： G06F16/9532 , G06Q30/06
CPC分类号： G06F16/9532 , G06Q30/0631
摘要： A computer-implemented method for suggesting keywords as a search term of a content item includes receiving, from a content provider, information about the content item in a database of content items. The method further includes generating a set of seed keywords related to the content item, and expanding the set of seed keywords to a plurality of candidate keywords. The plurality of candidate keywords are then scored based, at least in part, on an engagement metric measuring a user engagement with the content item in response to being presented with results from a search query comprising the candidate keyword. A candidate keyword is then selected from the plurality of candidate keywords based on the scoring, and stored relationally to the content item to define an audience for a recommendation about the content item, providing a suggestion to the content provider.
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