MAPPING RECIPE INGREDIENTS TO PRODUCTS

    公开(公告)号:US20220292568A1

    公开(公告)日:2022-09-15

    申请号:US17196879

    申请日:2021-03-09

    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.

    DETERMINING GENERIC ITEMS FOR ORDERS ON AN ONLINE CONCIERGE SYSTEM

    公开(公告)号:US20220414746A1

    公开(公告)日:2022-12-29

    申请号:US17929797

    申请日:2022-09-06

    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.

    QUERY REFORMULATIONS FOR AN ITEM GRAPH

    公开(公告)号:US20220277373A1

    公开(公告)日:2022-09-01

    申请号:US17188214

    申请日:2021-03-01

    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.

    BOOSTING SCORES FOR RANKING ITEMS MATCHING A SEARCH QUERY

    公开(公告)号:US20240104622A1

    公开(公告)日:2024-03-28

    申请号:US17955250

    申请日:2022-09-28

    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.

    MAPPING RECIPE INGREDIENTS TO PRODUCTS
    5.
    发明公开

    公开(公告)号:US20230260007A1

    公开(公告)日:2023-08-17

    申请号:US18139289

    申请日:2023-04-25

    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.

    PERSONALIZED RECOMMENDATION OF RECIPES INCLUDING ITEMS OFFERED BY AN ONLINE CONCIERGE SYSTEM BASED ON EMBEDDINGS FOR A USER AND FOR STORED RECIPES

    公开(公告)号:US20220358562A1

    公开(公告)日:2022-11-10

    申请号:US17682444

    申请日:2022-02-28

    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.

    ATTRIBUTE NODE WIDGETS IN SEARCH RESULTS FROM AN ITEM GRAPH

    公开(公告)号:US20230222162A1

    公开(公告)日:2023-07-13

    申请号:US18185091

    申请日:2023-03-16

    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.

    ATTRIBUTE NODE WIDGETS IN SEARCH RESULTS FROM AN ITEM GRAPH

    公开(公告)号:US20220179909A1

    公开(公告)日:2022-06-09

    申请号:US17112395

    申请日:2020-12-04

    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.

Patent Agency Ranking