Enterprise Architecture based Representation of Architecture and Design Patterns for Machine Learning Systems

Hironori Takeuchi, Takuo Doi, Hironori Washizaki, Satoshi Okuda, Nobukazu Yoshioka

研究成果: Conference contribution

抄録

In this study, we consider projects for the development of machine learning (ML) service systems that apply ML techniques to enterprise functions, and propose a method of representing the architecture and design patterns for ML service systems. Based on the proposed method, we represent the items described in the pattern documents as elements in the enterprise architecture modeling and derived a generic model for ML architecture and designed patterns. By applying the proposed method and the generic pattern model, we analyze an existing ML design pattern and represent it as a model. Through modeling practice, we confirm that an effective use scenario occurs when using the represented model during the project activities, and we can revise or enhance the pattern documents consistently by applying the model.

本文言語English
ホスト出版物のタイトルProceedings - 2021 IEEE 25th International Enterprise Distributed Object Computing Conference Workshops, EDOCW 2021
出版社Institute of Electrical and Electronics Engineers Inc.
ページ245-250
ページ数6
ISBN(電子版)9781665444880
DOI
出版ステータスPublished - 2021
イベント25th IEEE International Enterprise Distributed Object Computing Conference Workshops, EDOCW 2021 - Gold Coast, Australia
継続期間: 2021 10月 252021 10月 29

出版物シリーズ

名前Proceedings - IEEE International Enterprise Distributed Object Computing Workshop, EDOCW
ISSN(印刷版)1541-7719

Conference

Conference25th IEEE International Enterprise Distributed Object Computing Conference Workshops, EDOCW 2021
国/地域Australia
CityGold Coast
Period21/10/2521/10/29

ASJC Scopus subject areas

  • ハードウェアとアーキテクチャ
  • 理論的コンピュータサイエンス
  • ソフトウェア
  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用

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