Leveraging Unstructured Text Within the Context of Conversational Agents

Maria Phillips
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Abstract

We propose exploring alternative designs for a conversational agent developed as a tool to provide feedback within the education domain for pre-service teachers, students pursuing their teaching certificate, to practice their questioning skills in a given scenario. We utilize a component-based approach in the design of our conversational agent and this research focuses on proposing methods within the knowledge base component specifically leveraging unstructured text as the foundation of the knowledge base. Through leveraging unstructured text we intend to explore the possibilities of improving conversational agent response quality while minimizing resources required of domain experts in scenario development.
在会话代理的上下文中利用非结构化文本
我们建议探索对话代理的替代设计,将其作为一种工具,在教育领域为职前教师、追求教师证书的学生提供反馈,以在给定的场景中练习他们的提问技巧。我们在会话代理的设计中使用了基于组件的方法,本研究的重点是在知识库组件中提出方法,特别是利用非结构化文本作为知识库的基础。通过利用非结构化文本,我们打算探索提高会话代理响应质量的可能性,同时最大限度地减少场景开发领域专家所需的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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