Conversational case-based reasoning (CCBR) systems retrieve past cases that are similar to a current problem by eliciting situation descriptions in interactive dialogues with their users. To find out how such human-machine cooperation is put into practice, the present article reviews the CCBR literature and extracts a list of dialogue principles – interaction techniques by means of which CCBR systems communicate with their users. Seven dialogue principles are identified and explained: mixed initiative, question selection and ordering, dealing with abstraction and expertise, explanations, visualisation and highlighting, dialogue termination, and evaluation support. The results reveal that current CCBR systems already make great efforts to put user needs into the centre of the interaction. At the same time, the current implementation of dialogue principles that adjust CCBR systems to user needs raise questions about who should be in control of these adjustments, what levels of human-computer interaction should be adjusted, and what goals should guide adjustment decisions. Moreover, the present review highlights a number of limitations concerning the methodology and contents of CCBR research, and points out questions for future research on human-computer interaction in CCBR systems.

基于会话的案例推理（CCBR）系统通过在与用户的交互对话中引起情况描述来检索与当前问题相似的过去案例。为了了解如何实现这种人机协作，本文回顾了CCBR文献并提取了一系列对话原理-交互技术，CCBR系统通过这些技术与用户进行通信。确定并解释了七个对话原则：混合主动性，问题选择和排序，处理抽象和专业知识，解释，可视化和突出显示，对话终止和评估支持。结果表明，当前的CCBR系统已经做出了巨大的努力，将用户需求置于交互的中心。同时，当前根据CCBR系统调整以适应用户需求的对话原则的实施提出了以下问题：应该由谁来控制这些调整，应该调整哪些级别的人机交互以及应该由哪些目标来指导调整决策。此外，本综述突出了有关CCBR研究方法和内容的诸多限制，并指出了CCBR系统中人机交互的未来研究问题。