Privacy preserving machine learning extension model

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, are described for extending user groups using machine learning models while protecting user privacy and data security. In one aspect, a method includes receiving, for a web-based resource, a set of use...

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Bibliographic Details
Main Authors LEVINE JEFFREY CHARLES, PARANJPE DEEPA, HUANG WEI, LIU ZHENYU, BUSA-FEKETE ROBERT ISTVAN, WANG YIPEI
Format Patent
LanguageChinese
English
Published 03.05.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, are described for extending user groups using machine learning models while protecting user privacy and data security. In one aspect, a method includes receiving, for a web-based resource, a set of user group identifiers for a set of user interest groups, each user interest group including as a member one or more users requesting content from the web-based resource for a given time period. A seed user list is created that includes user identifiers of at least a portion of users in a set of user interest groups. A similar audience machine learning model is generated based on a set of one or more feature values corresponding to the one or more features of the user corresponding to the user identifier in the seed user list. A set of similar users is identified using the model. 描述了用于使用机器学习模型来在保护用户隐私和数据安全的同时扩展用户组的方法、系统和装置，包括编码在计算机存储介质上的计算机程序。在一个方面，一种方法包括针对基于web的资源接收用户兴趣组集合的用户组标识符集合，每个用户兴趣组包括作为成员的、在给定的时间段从基于web的资源请求内容
Bibliography:Application Number: CN202280059643