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2019 Vol.7, Issue 3 Preview Page
September 2019. pp. 27-37
기업에서는 다양한 프로세스들을 운용하는 방법으로는 프로세스라는 기술이 있다. 일반적으로 엔터프라이즈급 협업에서는 프로세스가 효율적으로 운용되어야 하고, 로컬 시스템 간의 상호운용은 필수이다. 그러나 지능형 클라우드 환경에서 로컬 시스템들은 그 목적에 따라 운영되고 있어서 엔터프라이즈급 협업 특성에 맞게 프로세스들을 실제로 운용하기가 어렵다. 또한, 기업형 환경에서 로컬 시스템 간의 프로세스를 운영하기 위해서는 서비스 기반의 전사적 데이터 통합이 필요하다.본 논문에서는 지능형 클라우드 환경에서 엔터프라이즈급 프로세스가 협업에서 효율적으로 운용되는 방법으로써 확장된 EMRA(Extended Metadata Registry Access) 기반의 시스템을 제안한다. 확장된 EMRA는 데이터 통합에 필요한 로컬 시스템 간의 상호운용이 가능하도록 한다. 또한, 프로세스 내부에 포함된 쿼리 간의 발생하는 메타데이터 정보 간의 매핑을 EMRA를 이용한다. 그리고 머신러닝을 이용하여 EMRA에서의 글로벌 스키마와 로컬 스키마 간의 매핑에 대한 분류 및 구성에 대한 기법을 제시한다.
The company has a process called technology as a way to operate a variety of processes. Typically the process is to be operated efficiently in an enterprise-class collaboration and interoperability between the local system is required. However, the local system in intelligent cloud environments are difficult to actually operate the processes to enterprise-class collaboration and operational characteristics in accordance with its purpose. In addition, the enterprise data integration services based is necessary to operate the process between the local system in the enterprise environment. In this paper, we propose a system based on (Extended Metadata Registry Access) EMRA extended by how efficiently management in enterprise-class collaboration processes in intelligent cloud environments. The extended EMRA enables interoperability between local systems for data integration. Also, EMRA is used to map the metadata information that occurs between the queries contained in the process. And, we propose a classification and composition method for mapping between global schema and local schema in EMRA using machine learning.
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  • Publisher :The Society of Convergence Knowledge
  • Publisher(Ko) :융복합지식학회
  • Journal Title :The Society of Convergence Knowledge Transactions
  • Journal Title(Ko) :융복합지식학회논문지
  • Volume : 7
  • No :3
  • Pages :27-37