Requirements Engineering for Machine Learning: A Review and Reflection

October 03, 2022 ยท The Cartographer ยท ๐Ÿ› 2022 IEEE 30th International Requirements Engineering Conference Workshops (REW)

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
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Authors Zhongyi Pei, Lin Liu, Chen Wang, Jianmin Wang arXiv ID 2210.00859 Category cs.SE: Software Engineering Cross-listed cs.LG Citations 35 Venue 2022 IEEE 30th International Requirements Engineering Conference Workshops (REW) Last Checked 2 days ago
Abstract
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.
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