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Building Dialogue Structure from Discourse Tree of a Question

机译:从一个问题的话语树建立对话结构

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In this section we propose a reasoning-based approach to a dialogue management for a customer support chat bot. To build a dialogue scenario, we analyze the discourse tree (DT) of an initial query of a customer support dialogue that is frequently complex and multi-sentence. We then enforce rhetorical agreement between DT of the initial query and that of the answers, requests and responses. The chat bot finds answers, which are not only relevant by topic but also suitable for a given step of a conversation and match the question by style, communication means, experience level and other domain-independent attributes. We evaluate a performance of proposed algorithm in car repair domain and observe a 5 to 10% improvement for single and three-step dialogues respectively, in comparison with baseline approaches to dialogue management.
机译:在本节中,我们提出了一种基于推理的对话管理方法,为客户支持聊天机BOT。为了构建对话场景,我们分析了客户支持对话的初始查询的话语树(DT),这些对话频繁复杂和多句子。然后,我们在初始查询的DT和答案,请求和响应中强制执行修辞协议。聊天机器人找到了答案,这不仅是主题的相关,而且还适用于对话的给定步骤,并通过样式,通信方式,体验级别和其他域独立属性匹配问题。我们评估了在汽车维修领域提出的算法的性能,并分别观察单个和三步对话的改进,与对话管理的基线方法相比。

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