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SYSTEMS AND METHODS FOR ENHANCED NATURAL LANGUAGE PROCESSING FOR MACHINE LEARNING CONVERSATIONS

机译:用于机器学习对话的增强自然语言处理的系统和方法

摘要

Systems and methods for variable field replacement are provided. Message templates include variable fields that can be populated with industry and client specific information through entity replacement, lexical replacement and phrase package selection. In addition to the generation of messages, the system may also be able to perform other actions that leverage external third-party systems. The templates may be drawn from a conversation library with hierarchical inheritance. Likewise, actions may leverage an action response library that links triggers in the response to required actions. Packet selection is based upon how closely the phrase fits a personality for the AI identity, and how well historically the phrase has performed. Lastly, while the AI systems disclosed herein have the ability to understand and respond to conversations in natural language format, this is computationally expensive. These AI systems may use an objective and intent based communication protocol when communicating with one another.
机译:提供了用于可变场替换的系统和方法。消息模板包括可变字段,可以通过实体替换,词法替换和短语包选择来填充行业和客户特定的信息。除了生成消息外,系统还可以执行利用外部第三方系统的其他操作。可以从具有分层继承的对话库中提取模板。同样,动作可以利用动作响应库,该库将响应中的触发器链接到所需动作。数据包的选择基于该短语与AI身份适合个性的紧密程度以及该短语在历史上的执行情况。最后,尽管本文公开的AI系统具有以自然语言格式理解和响应对话的能力,但这在计算上是昂贵的。这些AI系统在彼此通信时可以使用基于客观和意图的通信协议。

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