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Method and system for recommending domain-specific content based on recent user activity within a software application

机译:基于软件应用程序中最近的用户活动推荐特定于域的内容的方法和系统

摘要

Aspects of the present disclosure provide techniques for recommending content to users of an application based on a probability distribution over a set of articles generated from user activity history within the application. Embodiments include receiving a content request from a user of the application. A system retrieves, using a predictive model, predictive scores for items of content in response to the content request and user activity history within the application prior to the content request. The predictive model may be trained using user clickstream data for sessions executed within the application by a plurality of users, and information about actions performed within the application prior to a request may be correlated with content viewed by a user subsequent to the request. The system selects a group of the items of content to display to the user and displays the selected group of the items of content to the user.
机译:本公开的各方面提供了基于从应用程序内的用户活动历史中生成的一组物品上的概率分布推荐给应用程序的内容的技术。实施例包括从应用程序的用户接收内容请求。系统使用预测模型检索用于在内容请求之前应用程序内的内容请求和用户活动历史记录的内容项目的预测分数。可以使用多个用户在应用程序内执行的用户点心数据训练预测模型,并且关于在请求之前在应用程序之前执行的动作的信息可以与由请求之后的用户观看的内容相关联。系统选择要显示给用户的内容项组,并将所选择的内容项显示给用户。

著录项

  • 公开/公告号US10949432B1

    专利类型

  • 公开/公告日2021-03-16

    原文格式PDF

  • 申请/专利权人 INTUIT INC.;

    申请/专利号US201816213727

  • 发明设计人 DAVID GRAYSON;

    申请日2018-12-07

  • 分类号G06F16;G06F16/2457;H04L29/08;G06F9/451;G06N3/04;G06Q40;

  • 国家 US

  • 入库时间 2022-08-24 17:42:58

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