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Determining optimal workforce types to fulfill occupational roles in an organization based on occupational attributes

机译:确定最佳劳动力类型,以满足基于职业属性的组织职业角色

摘要

A device receives occupational activity descriptions and occupational role attributes, and processes the occupational activity descriptions to generate estimated occupational activity attribute values. The device trains a neural network model based on the estimated occupational activity attribute values to generate a trained neural network model, and receives a new activity description for a new role in an organization. The device processes the new activity description, with the trained neural network model, to generate estimated new activity attribute values, and processes the estimated new activity attribute values, with the logistic regression model, to generate probabilities that the new role is suitable for different workforce types. The device determines a workforce recommendation for the new role based on the probabilities that the new role is suitable for the different workforce types.
机译:设备接收职业活动描述和职业角色属性,并处理职业活动描述以生成估计的职业活动属性值。该器件基于估计的职业活动属性值列举神经网络模型以生成训练有素的神经网络模型,并在组织中接收新的活动描述以获得新的角色。设备处理新的活动描述,使用培训的神经网络模型来生成估计的新活动属性值,并处理估计的新活动属性值,以逻辑回归模型生成新角色适用于不同劳动力的概率类型。该设备根据新角色适用于不同的劳动力类型的概率来确定新角色的员工建议。

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