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Requirements Engineering for Machine Learning: A Review and Reflection

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arxiv 2210.00859 v1 pith:LNAJX6AN submitted 2022-10-03 cs.SE cs.LG

Requirements Engineering for Machine Learning: A Review and Reflection

classification cs.SE cs.LG
keywords learningmachinerequirementsdomainengineeringapplicationsbusinessindustrial
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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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