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COGNITIVE TRIGGERING OF HUMAN INTERACTION STRATEGIES TO FACILITATE COLLABORATION, PRODUCTIVITY, AND LEARNING

机译:人类互动策略的认知触发,以促进合作,生产力和学习

摘要

Embodiments are directed to a computer-implemented method that includes receiving, at a triggering system, input data about an environment. Machine learning (ML) algorithms extract features from the input data and analyze relationships among and between the features to generate user-interaction-readiness model of person-A's readiness to participate in a human interaction with other persons in the environment. The ML algorithms to apply real-world data about person-A to the user-interaction-readiness model to generate a first classification output comprising data representing person-A's readiness to participate in a human interaction with other persons in the environment. Based at least in part on a determination that person-A and another person(s) in the environment are interaction candidates, the triggering system triggers the initiation of human interaction strategies configured to facilitate human interactions between person-A and the previously identified another person(s) in the environment.
机译:实施例针对一种计算机实现的方法,该方法包括在触发系统处接收关于环境的输入数据。机器学习(ML)算法从输入数据中提取特征,并分析这些特征之间的关系,以生成A人准备参与与环境中其他人的人机交互的用户交互准备模型。 ML算法将有关A人的真实世界数据应用于用户交互准备模型,以生成第一分类输出,该输出包括代表A人准备参与与环境中其他人的人际互动的数据。至少部分地基于确定环境中的人A和另一个人是交互候选者,触发系统触发人类交互策略的启动,该交互策略被配置为促进人A和先前识别的另一个人之间的人际交互(s)在环境中。

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