论文标题
在寻求信息对话中的混合计划和合作分析
An Analysis of Mixed Initiative and Collaboration in Information-Seeking Dialogues
论文作者
论文摘要
进行混合互动的能力是对话搜索系统的核心要求之一。如何实现这一目标是很众所周知的。我们提出了一组无监督的指标，称为“对话”，该指标通过比较词汇和话语类型的分布来强调每个对话参与者扮演的角色。将ConverationShape用作镜头，我们仔细研究了几个对话搜索数据集，并将它们与其他对话数据集进行比较，以更好地了解其代表的对话交互的类型，要么由信息寻求者或助手驱动。我们发现，相同类型的人类对话的对话偏差可预测人机对话的质量。
The ability to engage in mixed-initiative interaction is one of the core requirements for a conversational search system. How to achieve this is poorly understood. We propose a set of unsupervised metrics, termed ConversationShape, that highlights the role each of the conversation participants plays by comparing the distribution of vocabulary and utterance types. Using ConversationShape as a lens, we take a closer look at several conversational search datasets and compare them with other dialogue datasets to better understand the types of dialogue interaction they represent, either driven by the information seeker or the assistant. We discover that deviations from the ConversationShape of a human-human dialogue of the same type is predictive of the quality of a human-machine dialogue.
