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    PROVIDING AND DISPLAYING SEARCH RESULTS IN RESPONSE TO A QUERY
    2.
    发明公开
    PROVIDING AND DISPLAYING SEARCH RESULTS IN RESPONSE TO A QUERY 审中-公开

    公开(公告)号：US20240249335A1

    公开(公告)日：2024-07-25

    申请号：US18159357

    申请日：2023-01-25

    申请人： Maplebear Inc. (dba Instacart)

    发明人： Taesik Na ,  Vinesh Reddy Gudla ,  Xiao Xiao

    IPC分类号： G06Q30/0601 ,  G06F16/9535 ,  G06Q30/0201

    CPC分类号： G06Q30/0631 ,  G06F16/9535 ,  G06Q30/0201

    摘要： An online system displays search results in response to a query by receiving a query from a customer. An online system accesses a set of candidate items and computes a relevance score and personalization score for each item. The online system computes the relevance score based on query data and item data and may normalize the relevance score. The online system computes the personalization score based on item data, such as an item embedding, and user data, such as a user embedding. The online system computes a query specificity score and adjusts the personalization score with the query specificity score such that generic queries have high personalization scores and specific queries have low personalization scores. The online system combines the relevance and personalization scores for each candidate item into a ranking score and displays the candidate items to the customer based on their ranking scores.

    MACHINE LEARNED MODELS FOR SEARCH AND RECOMMENDATIONS
    3.
    发明公开
    MACHINE LEARNED MODELS FOR SEARCH AND RECOMMENDATIONS 审中-公开

    公开(公告)号：US20240241897A1

    公开(公告)日：2024-07-18

    申请号：US18415551

    申请日：2024-01-17

    申请人： Maplebear Inc.

    发明人： Haixun Wang ,  Taesik Na ,  Li Tan ,  Jian Li ,  Xiao Xiao

    IPC分类号： G06F16/33 ,  G06F16/338 ,  G06N20/00

    CPC分类号： G06F16/3344 ,  G06F16/338 ,  G06N20/00

    摘要： A system may generate a prompt based in part on a search query from a customer client device. The prompt instructs a machine learned model to provide item predictions. And the model was trained by: converting structured data describing items of an online catalog to annotated text data (unstructured data), generating training examples based in part on the annotated text data, and training the model using the training examples. The system may receive item predictions generated by the prompt being applied to the machine learned model, the item predictions may have corresponding item identifiers. The item predictions are processed to identify a recommended item from the item predictions. The processing includes determining item information for the recommended item using an item identifier associated with the recommended item. The item information is provided to the customer client device.

    DETERMINING SEARCH RESULTS FOR AN ONLINE SHOPPING CONCIERGE PLATFORM
    6.
    发明公开
    DETERMINING SEARCH RESULTS FOR AN ONLINE SHOPPING CONCIERGE PLATFORM 审中-公开

    公开(公告)号：US20240177212A1

    公开(公告)日：2024-05-30

    申请号：US18072353

    申请日：2022-11-30

    申请人： Maplebear Inc. (dba Instacart)

    发明人： Aditya Subramanian ,  Prakash Putta ,  Tejaswi Tenneti ,  Jonathan Lennart Bender ,  Xiao Xiao ,  Taesik Na

    IPC分类号： G06Q30/0601

    CPC分类号： G06Q30/0631

    摘要： To determine search results for an online shopping concierge platform, the platform may receive, from a computing device associated with a customer of an online shopping concierge platform, data describing one or more search parameters input by the customer; identify, based at least in part on the data describing the search parameter(s), products offered by the online shopping concierge platform that are at least in part responsive to the search parameter(s); and determine, for each product and based at least in part on one or more machine learning (ML) models, a relevance of the product to one or more taxonomy levels of a product catalog associated with the online shopping concierge platform, a likelihood that the customer would be offended by inclusion of the product amongst displayed responsive search results, and/or the like.