SYNTHETIC DATA GENERATION FOR SERVICE RECOMMENDATION

    公开(公告)号:US20250124488A1

    公开(公告)日:2025-04-17

    申请号:US19002124

    申请日:2024-12-26

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for synthetic data generation for service recommendation models. One of the methods includes generating a plurality of synthetic data items, each synthetic data item including user data, context data, service data of a service, and user action data characterizing one or more user actions with respect to the service; for each synthetic data item of the plurality of synthetic data items, processing the synthetic data item using an evaluator to generate a score indicating quality of the synthetic data item; selecting a subset of synthetic data items from the plurality of synthetic data items; and providing the subset of synthetic data items into a service recommendation model for recommending one or more services to one or more users based on the subset of synthetic data items.

    Website similarity determination
    2.
    发明授权

    公开(公告)号:US11675873B1

    公开(公告)日:2023-06-13

    申请号:US17809513

    申请日:2022-06-28

    Applicant: Lemon Inc.

    CPC classification number: G06F16/958 G06F16/954

    Abstract: There are provided methods, devices, and computer program products for similarity determination. In a method, first and second access data are obtained for a first and a second group of users who access a first and a second website, respectively. A first and a second jump path are generated for the first and second groups of users based on the first and second access data, respectively. The first and second jump paths describe access history for the first and second groups of users among webpages in the first and second websites, respectively. A similarity is determined between the first and second websites based on the first and second jump paths. Here, access data are used for similarity determination and unvisited webpages are not considered in the similarity determination. Therefore, the computation workload may be lowered, and the noise caused by the unvisited webpages may be reduced.

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