首页> 外国专利> MACHINE-LEARNING PROCESSING AT NATIVE-LOCATION STORAGE SYSTEM TO GENERATE COLLECTIONS ACTION PLAN

MACHINE-LEARNING PROCESSING AT NATIVE-LOCATION STORAGE SYSTEM TO GENERATE COLLECTIONS ACTION PLAN

机译:本地存储系统中的机器学习过程以生成集合行动计划

摘要

Techniques are disclosed for using machine-learning processing for generating resource-allocation specifications. A first data set may be received from a first data source. The first data set can include a first resource request and a first timestamp associated with entities. A second data set can be received from a second data source that includes communication data and allocation data associated with the entities. Target characteristics may be defined for training instances. The training instances can be used to train a machine-learning model using the first data set and the second data set. A third data set may be accessed and used to generate a user session within which, the trained machine-learning model may execute to generate a resource-allocation specification. The resource-allocation specification including a communication schedule. One or more communications compliant with the communication schedule may be output to an entity.
机译:公开了用于使用机器学习处理来生成资源分配规范的技术。可以从第一数据源接收第一数据集。第一数据集可以包括与实体相关联的第一资源请求和第一时间戳。可以从第二数据源接收第二数据集,该第二数据集包括与实体相关联的通信数据和分配数据。可以为训练实例定义目标特征。训练实例可以用于使用第一数据集和第二数据集来训练机器学习模型。可以访问第三数据集并用于生成用户会话,在该用户会话中,受过训练的机器学习模型可以执行以生成资源分配规范。资源分配规范包括通信时间表。可以将符合通信时间表的一个或多个通信输出到实体。

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