-An Algorithm for Cube-based Mining Association Rules and Application to Database Marketing

데이터 큐브를 이용한 연관규칙 발견 알고리즘

  • 한경록 (한양대학교 산업공학과) ;
  • 김재련 (한양대학교 산업공학과)
  • Published : 2000.02.01


The problem of discovering association rules is an emerging research area, whose goal is to extract significant patterns or interesting rules from large databases and several algorithms for mining association rules have been applied to item-oriented sales transaction databases. Data warehouses and OLAP engines are expected to be widely available. OLAP and data mining are complementary; both are important parts of exploiting data. Our study shows that data cube is an efficient structure for mining association rules. OLAP databases are expected to be a major platform for data mining in the future. In this paper, we present an efficient and effective algorithm for mining association rules using data cube. The algorithm can be applicable to enhance the power of competitiveness of business organizations by providing rapid decision support and efficient database marketing through customer segmentation.