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

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

研究成果: Conference article同行評審

38 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)505-510
頁數6
期刊Proceedings - IEEE Computer Society's International Computer Software and Applications Conference
出版狀態Published - 2001 1月 1
事件25th Annual International Computer Software and Applications Conference (COMPSAC)2001 - Chicago, IL, United States
持續時間: 2001 10月 82001 10月 12

All Science Journal Classification (ASJC) codes

  • 軟體
  • 電腦科學應用

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