阅读说明：本技术 基于网络分发历史从数字媒体的储存库生成对应于预测的分发类别的数字媒体群集 (Generating digital media clusters corresponding to predicted distribution categories from a repository of digital media based on network distribution history ) 是由 赵跃 王宇 威廉·塞谬尔·贝利 马里·谢布莱 于 2020-03-30 设计创作，主要内容包括：本公开涉及用于基于网络分发历史从数字媒体的储存库中生成对应于预测的分发类别的准确数字媒体群集的系统、非暂时性计算机可读介质和方法。例如,数字媒体聚类系统可以(基于用户的网络账户的网络分发历史)在远程服务器处应用机器学习模型,从而为未来的电子通信生成预测的分发类别。远程服务器可以向用户客户端设备提供预测的分发类别,用于对存储在客户端设备处的数字媒体进行安全的本地分析。基于预测的分发类别和存储的数字媒体,客户端设备可以建议数字媒体项经由网络系统进行分发。因此,所公开的系统可以在不向远程服务器提供关于存储在客户端设备处的数字媒体项的任何信息的情况下展示数字媒体内容。(The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating accurate digital media clusters corresponding to predicted distribution categories from a repository of digital media based on network distribution history. For example, the digital media clustering system may apply a machine learning model at a remote server (based on the network distribution history of the user's network account) to generate predicted distribution categories for future electronic communications. The remote server may provide the predicted distribution category to the user client device for secure local analysis of digital media stored at the client device. Based on the predicted distribution category and the stored digital media, the client device may suggest that the digital media item be distributed via the network system. Thus, the disclosed system can present digital media content without providing any information to a remote server regarding digital media items stored at a client device.)