论文标题
关注我：针对目标驱动的推荐对话系统的对话计划
Follow Me: Conversation Planning for Target-driven Recommendation Dialogue Systems
论文作者
论文摘要
建议对话系统旨在与用户建立社会纽带并提供高质量的建议。本文向前迈进了一个有希望的范式，称为目标驱动的推荐对话系统，该系统非常需要尚未探索。我们专注于如何自然地引导用户通过对话逐渐接受指定的目标。为此，我们提出了一个目标驱动的对话计划（TCP）框架，以计划一系列对话动作和主题，并推动系统在不同的对话阶段之间进行过境。然后，我们将TCP与计划的内容一起使用，以指导对话生成。实验结果表明，我们的对话计划显着提高了目标驱动的建议对话系统的性能。
Recommendation dialogue systems aim to build social bonds with users and provide high-quality recommendations. This paper pushes forward towards a promising paradigm called target-driven recommendation dialogue systems, which is highly desired yet under-explored. We focus on how to naturally lead users to accept the designated targets gradually through conversations. To this end, we propose a Target-driven Conversation Planning (TCP) framework to plan a sequence of dialogue actions and topics, driving the system to transit between different conversation stages proactively. We then apply our TCP with planned content to guide dialogue generation. Experimental results show that our conversation planning significantly improves the performance of target-driven recommendation dialogue systems.
