基于对话的过程决策自动化
Dialog-based Automation of Decision Making in Processes
摘要：
聊天机器人的使用已经普及，在行业中产生了极大的兴趣，因为在执行过程中自动化任务的可能性。聊天机器人的实现无论多么简单，都是一项复杂的工作，涉及许多低级细节，这使得它成为一项耗时且容易出错的任务。在本文中，我们旨在促进决策支持聊天机器人的开发，这些机器人可以指导用户或帮助知识工作者根据不同流程参与者之间的交互做出决策，旨在减少人类工作人员的工作量，例如，在医疗保健中识别疾病的第一个症状。我们的工作涉及一种方法，从现有的DMN模型中半自动地系统地构建决策支持聊天机器人。聊天机器人旨在利用自然语言理解平台，如Dialogflow或LUIS。我们基于我们的方法实现了Dialogflow聊天机器人原型，并进行了试点测试，揭示了对所开发聊天机器人的可用性和吸引力的见解。
英文摘要：
The use of chatbots has spread, generating great interest in the industry for the possibility of automating tasks within the execution of their processes. The implementation of chatbots, however simple, is a complex endeavor that involves many low-level details, which makes it a time-consuming and error-prone task. In this paper we aim at facilitating the development of decision-support chatbots that guide users or help knowledge workers to make decisions based on interactions between different process participants, aiming at decreasing the workload of human workers, for example, in healthcare to identify the first symptoms of a disease. Our work concerns a methodology to systematically build decision-support chatbots, semi-automatically, from existing DMN models. Chatbots are designed to leverage natural language understanding platforms, such as Dialogflow or LUIS. We implemented Dialogflow chatbot prototypes based on our methodology and performed a pilot test that revealed insights into the usability and appeal of the chatbots developed.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
