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A Composite Cluster Analysis Approach for Component Classification

컴포넌트 분류를 위한 복합 클러스터 분석 방법

  • 이성구 (한신대학교 컴퓨터정보소프트웨어학부)
  • Published : 2007.02.28

Abstract

Various classification methods have been developed to reuse components. These classification methods enable the user to access the needed components quickly and easily. Conventional classification approaches include the following problems: a labor-intensive domain analysis effort to build a classification structure, the representation of the inter-component relationships, difficult to maintain as the domain evolves, and applied to a limited domain. In order to solve these problems, this paper describes a composite cluster analysis approach for component classification. The cluster analysis approach is a combination of a hierarchical cluster analysis method, which generates a stable clustering structure automatically, and a non-hierarchical cluster analysis concept, which classifies new components automatically. The clustering information generated from the proposed approach can support the domain analysis process.

컴포넌트 재사용을 위해 다양한 분류 방법들이 개발되어 왔다. 이러한 분류 방법들은 사용자가 필요로 하는 컴포넌트들을 쉽고 빠르게 접근하는 것을 돕는다. 전통적인 분류 방법들은 분류 구조 생성을 위한 도메인 분석 노력, 컴포넌트 사이의 관계 표현, 도메인 진화에 따른 분류 구조 유지 보수의 어려움, 그리고 한정된 도메인 적용과 같은 문제들을 포함한다. 본 논문은 이러한 문제들을 언급하기 위해 복합 클러스터 분석 기반의 컴포넌트 분류 방법에 대해 묘사한다. 안정적인 분류 구조 자동 생성을 위해 계층 클러스터 분석 방법과 새로운 컴포넌트의 자동 분류에 대해 비계층 클러스터 분석 개념은 결합된다. 제안된 방법에 의해 생성된 클러스터 정보는 관련 컴포넌트들에 대한 도메인 분석 과정을 지원할 수 있다.

Keywords

References

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