论文标题
低成本，可控制且可解释的面向任务的聊天机器人：以现实世界的售后服务为例
A Low-Cost, Controllable and Interpretable Task-Oriented Chatbot: With Real-World After-Sale Services as Example
论文作者
论文摘要
尽管在行业中广泛使用，但传统的以任务为导向的对话系统具有三个瓶颈：（i）困难的本体论构建（例如，意图和插槽）； （ii）可控性和解释性差； （iii）渴望注释。在本文中，我们建议用更简单的概念来表示对话操作的话语，然后在该概念上构建树结构的任务流，并进一步构建以任务流为核心组件的任务流聊天机器人。提出了一个框架，可以从大规模对话中自动构建任务流并在线部署。我们对现实世界售后服务服务的实验表明，任务流可以满足主要需求，并有效地减轻了开发人员的负担。
Though widely used in industry, traditional task-oriented dialogue systems suffer from three bottlenecks: (i) difficult ontology construction (e.g., intents and slots); (ii) poor controllability and interpretability; (iii) annotation-hungry. In this paper, we propose to represent utterance with a simpler concept named Dialogue Action, upon which we construct a tree-structured TaskFlow and further build task-oriented chatbot with TaskFlow as core component. A framework is presented to automatically construct TaskFlow from large-scale dialogues and deploy online. Our experiments on real-world after-sale customer services show TaskFlow can satisfy the major needs, as well as reduce the developer burden effectively.
