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    • 4. 发明授权
    • Systems and methods for implementing a machine-learning agent to retrieve information in response to a message
    • 用于实现机器学习代理以响应于消息来检索信息的系统和方法
    • US08533132B2
    • 2013-09-10
    • US12841714
    • 2010-07-22
    • John ZimmermanAnthony TomasicIan Hargraves
    • John ZimmermanAnthony TomasicIan Hargraves
    • G06F15/18
    • G06N99/005
    • Mixed-initiative message-augmenting agent systems and methods that provide users with tools that allow them to respond to messages, such as email messages, containing requests for information or otherwise requiring responses that require information that needs to be retrieved from one or more data sources. The systems and methods allow users to train machine-learning agents how to retrieve and present information in responses to like messages so that the machine-learning agents can eventually automatedly generate responses with minimal involvement by the users. Embodiments of the systems and methods allow users to build message-augmenting forms containing the desired information for responding to messages and to demonstrate to the machine-learning agents where to retrieve pertinent information for populating the forms. Embodiments of the systems and methods allow users to modify and repair automatically generated forms to continually improve the knowledge of the machine-learning agents.
    • 混合主动消息增强代理系统和方法,为用户提供允许他们响应包含信息请求的消息(如电子邮件)或需要需要从一个或多个数据源检索到信息的响应的工具 。 系统和方法允许用户训练机器学习代理如何在类似消息的响应中检索和呈现信息,使得机器学习代理最终能够以最少的用户参与自动生成响应。 系统和方法的实施例允许用户构建包含用于响应消息的期望信息的消息增加表单,并向机器学习代理程序证明哪里可以检索用于填充表单的相关信息。 系统和方法的实施例允许用户修改和修复自动生成的表单,以不断地改进机器学习代理的知识。
    • 7. 发明申请
    • Systems and Methods for Implementing a Machine-Learning Agent to Retrieve Information in Response to a Message
    • 用于实现机器学习代理以响应消息检索信息的系统和方法
    • US20110022552A1
    • 2011-01-27
    • US12841714
    • 2010-07-22
    • John ZimmermanAnthony TomasicIan Hargraves
    • John ZimmermanAnthony TomasicIan Hargraves
    • G06F15/18G06F17/00G06F15/16
    • G06N99/005
    • Mixed-initiative message-augmenting agent systems and methods that provide users with tools that allow them to respond to messages, such as email messages, containing requests for information or otherwise requiring responses that require information that needs to be retrieved from one or more data sources. The systems and methods allow users to train machine-learning agents how to retrieve and present information in responses to like messages so that the machine-learning agents can eventually automatedly generate responses with minimal involvement by the users. Embodiments of the systems and methods allow users to build message-augmenting forms containing the desired information for responding to messages and to demonstrate to the machine-learning agents where to retrieve pertinent information for populating the forms. Embodiments of the systems and methods allow users to modify and repair automatically generated forms to continually improve the knowledge of the machine-learning agents.
    • 混合主动消息增强代理系统和方法,为用户提供允许他们响应包含信息请求的消息(例如电子邮件)或需要需要从一个或多个数据源检索到信息的响应的工具 。 系统和方法允许用户训练机器学习代理如何在类似消息的响应中检索和呈现信息,使得机器学习代理最终能够以最少的用户参与自动生成响应。 系统和方法的实施例允许用户构建包含用于响应消息的期望信息的消息增加表单,并向机器学习代理程序证明哪里可以检索用于填充表单的相关信息。 系统和方法的实施例允许用户修改和修复自动生成的表单,以不断地改进机器学习代理的知识。