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.
|Number of pages||6|
|Journal||Proceedings - IEEE Computer Society's International Computer Software and Applications Conference|
|Publication status||Published - 2001 Jan 1|
|Event||25th Annual International Computer Software and Applications Conference (COMPSAC)2001 - Chicago, IL, United States|
Duration: 2001 Oct 8 → 2001 Oct 12
All Science Journal Classification (ASJC) codes
- Computer Science Applications