Information Systems Review (경영정보학연구)

The Korea Society of Management Information Systems (한국경영정보학회)
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A Recursive Procedure for Mining Continuous Change of Customer Purchase Behavior

고객 구매행태의 지속적 변화 파악을 위한 재귀적 변화발견 방법

  • 김재경 (경희대학교 경영대학) ;
  • 채경희 (경희대학교 경영대학) ;
  • 최주철 (경희대학교 경영대학) ;
  • 송희석 (한남대학교 경영정보학과) ;
  • 조영빈 (건국대학교 사회과학대학 경영학과)
  • Published : 2006.08.30
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Abstract

Association Rule Mining has been successfully used for mining knowledge in static environment but it provides limited features to discovery time-dependent knowledge from multi-point data set. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different multi-point snapshots. This paper proposes a procedure named 'Recursive Change Mining' for detecting continuous change of customer purchase behavior. The Recursive Change Mining Procedure is basically extended association rule mining and it assures to discover continuous and repetitive changes from data sets which collected at multi-periods. A case study on L department store is also provided.

데이터 마이닝의 연관성규칙 분석 기법(Association Rule Mining)은 현실문제에의 많은 활용에도 불구하고 시간의 흐름에 대한 변화 파악 및 분석에서는 한계를 가지고 있다. 본 연구에서는 기존의 두 시점에서의 고객 행위 변화 파악 기법을 재귀적 방법을 통하여 다시점으로 확장하여 분석할 수 있는 방법론을 제시한다. 즉, 본 연구에서는 연관성규칙의 패턴 및 변화의 추세를 장기간에 걸쳐 지속적으로 관찰함으로써, 고객의 일시적인 변화보다는 지속적인 행위 변화를 관찰할 수 있도록 하는 방법론을 구성한다. 방법론을 검증하기 위해 L백화점의 4년간의 구매관련 데이터를 분석하여 그 결과를 제시하고 있다.

Keywords

References

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