Today, many industrial processes are undergoing digital transformation, which often requires the integration of well-understood domain models and state-of-the-art machine learning technology in business processes. However, requirements elicitation and design decision making about when, where and how to embed various domain models and end-to-end machine learning techniques properly into a given business workflow requires further exploration. This paper aims to provide an overview of the requirements engineering process for machine learning applications in terms of cross domain collaborations. We first review the literature on requirements engineering for machine learning, and then go through the collaborative requirements analysis process step-by-step. An example case of industrial data-driven intelligence applications is also discussed in relation to the aforementioned steps.
翻译:今天,许多工业流程正在经历数字转型,这往往需要将广为人知的域模型和最先进的机器学习技术纳入业务流程,然而,需要进一步探讨各种要求的产生和设计决策,以确定何时、何地以及如何适当地将各种域模型和端对端机学习技术纳入特定业务流程,本文件旨在概述在跨域协作方面机器学习应用的工程程序要求。我们首先审查关于机器学习要求工程的文献,然后逐步通过合作要求分析过程。还结合上述步骤讨论了工业数据驱动情报应用的例子。