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MULTI-TURN CROSS-DOMAIN NATURAL LANGUAGE UNDERSTANDING SYSTEMS, BUILDING PLATFORMS, AND METHODS

机译:多匝跨域自然语言理解系统,建筑平台和方法

摘要

Multi-turn cross-domain natural language understanding (NLU) systems and platforms for building the multi-turn cross-domain NLU system are provided. Further, methods for using and building the multi-turn cross-domain NLU system are provided. More specifically, the multi-turn cross-domain NLU system supports multi-turn bot/agent/application scenarios for new domains without having to select a task definition and/or define a new schema during the building of the NLU system. Accordingly, the platform for building the multi-turn cross-domain NLU system that does not require the builder to select a task and/or build a schema for a selected task provides an easy to use, cost effective, and efficient service for building a NLU system. Further, the multi-turn cross-domain NLU system provides a more versatile NLU system than previously utilized NLU systems that were trained for and limited to a selected task and/or domain.
机译:提供了用于构建多匝跨域NLU系统的多匝跨域自然语言理解(NLU)系统和平台。此外,提供了使用和构建多匝跨域NLU系统的方法。更具体地说,多回转跨域NLU系统支持新域的多回转bot /代理/应用程序场景,而无需在NLU系统构建过程中选择任务定义和/或定义新方案。因此,用于构建多匝跨域NLU系统的平台不需要构建者选择任务和/或为选定的任务构建模式,该平台提供了易于使用,具有成本效益和高效的服务来构建应用程序。 NLU系统。此外,与先前使用的针对特定任务和/或领域进行训练并限于所选任务和/或领域的NLU系统相比,多匝跨域NLU系统提供了更加通用的NLU系统。

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