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System and method for making content-based recommendations using a user profile likelihood model

机译:使用用户简档可能性模型进行基于内容的建议的系统和方法

摘要

Aspects of the present disclosure involve systems, methods, devices, and the like for making content-based recommendations using a user profile likelihood model. In one embodiment, a system is introduced that includes a plurality of models and storage units for storing, managing, and transforming product and user profile data. The system can also include a recommendation engine designed to determine a probability that a product is relevant to a user based on a user profile. In another embodiment, the probability that a product is relevant to a user may be determined based in part on a frequency of interactions with a product and a time of interaction with the products.
机译:本公开的各方面涉及用于使用用户简档似然模型进行基于内容的建议的系统,方法,设备等。在一个实施例中,引入系统,其包括多个模型和存储单元,用于存储,管理和转换产品和用户简档数据。该系统还可以包括推荐引擎,该推荐引擎旨在基于用户简档确定产品与用户相关的概率。在另一个实施例中,产品与用户相关的概率可以部分地基于与产品的交互的频率和与产品交互的频率来确定。

著录项

  • 公开/公告号US10984461B2

    专利类型

  • 公开/公告日2021-04-20

    原文格式PDF

  • 申请/专利权人 PAYPAL INC.;

    申请/专利号US201816232907

  • 发明设计人 ZEXI MAO;

    申请日2018-12-26

  • 分类号G06Q30/06;G06N7;

  • 国家 US

  • 入库时间 2022-08-24 18:17:06

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