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사후확률에 기반한 근사 규칙의 생성

Creation of Approximate Rules based on Posterior Probability

  • 투고 : 2015.07.10
  • 심사 : 2015.10.09
  • 발행 : 2015.10.31

초록

본 논문에서는 데이터베이스의 정보시스템을 구성하는 속성을 감축하여 빠른 검색을 보장하는 제어규칙의 생성에 관한 연구이다. 일반적으로 정보시스템에는 불필요한 많은 속성들이 존재하고 있다. 이때 정보시스템의 객체들이 비일관적일 경우에는 응답의 정확성을 기대하기 어렵게 된다. 그러므로 본 논문에서는 러프엔트로피의 개념과 베이지언 사후확률을 적용하여 불필요한 속성을 제거하여 정보시스템을 간결화 하는데 주안점을 두었다. 제안된 알고리즘에서는 러프이론에 기반한 최적의 리덕트를 생성하는 과정에서 사후확률을 적용하여 결정속성에 대한 조건속성의 함의를 러프엔트로피의 척도로 비교하여 영향력이 약한 속성을 제거하여 제어규칙을 간결하게 표현할 수 있다. 제안된 알고리즘을 신입사원의 채용에 적용하여 지식감축의 효용성을 보인다.

In this paper the patterns of information system is reduced so that control rules can guarantee fast response of queries in database. Generally an information system includes many kinds of necessary and unnecessary attribute. In particular, inconsistent information system is less likely to acquire the accuracy of response. Hence we are interested in the simple and understandable rules that can represent useful patterns by means of rough entropy and Bayesian posterior probability. We propose an algorithm which can reduce control rules to a minimum without inadequate patterns such that the implication between condition attributes and decision attributes is measured through the framework of rough entropy. Subsequently the validation of the proposed algorithm is showed through test information system of new employees appointment.

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참고문헌

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