An Efficient Clustering Algorithm for Market Basket Data Based on Small Large Ratios

Authors:
Ching-Huang Yun;Kun-Ta Chuang;Ming-Syan Chen
Affiliations:
-;-;-
Venue:
COMPSAC '01 Proceedings of the 25th International Computer Software and Applications Conference on Invigorating Software Development
Year:
2001

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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.