Requirements Engineering for Machine Learning: A Review and Reflection
October 03, 2022 ยท The Cartographer ยท ๐ 2022 IEEE 30th International Requirements Engineering Conference Workshops (REW)
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"Title-pattern auto-detect: Requirements Engineering for Machine Learning: A Review and Reflection"
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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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