Transactions Clustering based on Item Similarity

아이템의 유사도를 고려한 트랜잭션 클러스터링

  • 이상욱 (한양대학교 산업공학과) ;
  • 김재련 (한양대학교 산업공학과)
  • Published : 2002.11.01

Abstract

Clustering is a data mining method, which consists in discovering interesting data distributions in very large databases. In traditional data clustering, similarity of a cluster of object is measured by pairwise similarity of objects in that paper. In view of the nature of clustering transactions, we devise in this paper a novel measurement called item similarity and utilize this to perform clustering. With this item similarity measurement, we develop an efficient clustering algorithm for target marketing in each group.

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