Building Dialogue Structure from Discourse Tree of a Question

Boris A. Galitsky
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引用次数: 6

Abstract

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.
从问题语篇树构建对话结构
在本节中,我们提出一种基于推理的方法来管理客户支持聊天机器人的对话。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),该对话通常是复杂和多句的。然后,我们在初始查询的DT与答案、请求和响应的DT之间强制执行修辞一致。聊天机器人找到的答案不仅与话题相关,而且适合对话的给定步骤,并根据风格、沟通方式、经验水平和其他与领域无关的属性匹配问题。我们评估了所提出的算法在汽车维修领域的性能,并观察到与对话管理的基线方法相比,单步和三步对话分别提高了5%到10%。
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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