Abstract
In this study, we consider project models for machine learning-based service systems. We introduce the enterprise architecture (EA) modeling approach and represent these models by using the business layer elements, application layer elements, and motivation extensions defined in ArchiMate. Through a real project case, we demonstrate the relationships between the project models and discuss model use cases.
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Acknowledgement
This work was supported by JSPS Grant-in-Aid for Scientific Research (KAKENHI), Grant Number: JP19K20416 and JST-Mirai Project (Engineerable AI Techniques for Practical Applications of High-Quality Machine Learning-based Systems), Grant Number: JPMJMI20B8.
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Takeuchi, H., Ito, Y., Nishiyama, R., Isomura, T. (2021). Modeling of Machine Learning Projects Using ArchiMate. In: Zimmermann, A., Howlett, R.J., Jain, L.C., Schmidt, R. (eds) Human Centred Intelligent Systems . KES-HCIS 2021. Smart Innovation, Systems and Technologies, vol 244. Springer, Singapore. https://doi.org/10.1007/978-981-16-3264-8_21
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DOI: https://doi.org/10.1007/978-981-16-3264-8_21
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