An efficient clustering algorithm for market basket data based on small large ratios

C. H. Yun, Kun-Ta Chuang, M. S. Chen

Research output: Contribution to journalConference articlepeer-review

33 Citations (Scopus)

Abstract

In this paper, we devise an efficient algorithm for clustering market-basket data items. In view of the nature of clustering market basket data, we devise in this paper a novel measurement, called the small-large (abbreviated as SL) ratio, and utilize this ratio to perform the clustering. With this SL ratio measurement, we develop an efficient clustering algorithm for data items to minimize the SL ratio in each group. The proposed algorithm not only incurs an execution time that is significantly smaller than that by prior work but also leads to the clustering results of very good quality.

Original languageEnglish
Pages (from-to)505-510
Number of pages6
JournalProceedings - IEEE Computer Society's International Computer Software and Applications Conference
Publication statusPublished - 2001 Jan 1
Event25th Annual International Computer Software and Applications Conference (COMPSAC)2001 - Chicago, IL, United States
Duration: 2001 Oct 82001 Oct 12

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications

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