EXTRACTING AN EMOTIONAL STATE FROM DEVICE DATA

Representative embodiments disclose mechanisms to extract an emotional state from contextual user data and public use data collected from one or more devices and/or services. The contextual and publicdata are combined into an enriched data set. An emotional model, tailored to the user, extracts an emotional state form the enriched data set based on one or more machine learning techniques. The emotional state is used to identify one or more actions that change operation of one or more devices and/or services in order to achieve a change in emotional state, compatibility between the emotional state and device and/or service interaction with the user, or both. Implicit and/or explicit feedback is collected and used to change prediction of the emotional state and/or selection of the actions. 表示性实施例公开了从由一个或多个设备和/或服务收集的上下文用户数据和公共使用数据提取情绪状态的机制。上下文数据和公共数据被组合成丰富数据集。对用户定制的情绪模型基于一个或多个机器学习技术从丰富数据集提取情绪状态。情绪状态被用来标识改变一个或多个设备和/或服务的操作的一个或多个动作以便实现情绪状态的变化、情绪状态与和用户的设备和/或服务交互之间的兼容性或两者。隐式和/或显式反馈被收集并被用来改变对情绪状态的预测和/或动作的选择。