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Woong-Kee LOH Yang-Sae MOON Heejune AHN
We propose a robust and efficient algorithm called ROCKET for clustering large-scale transaction databases. ROCKET is a divisive hierarchical algorithm that makes the most of recent hardware architecture. ROCKET handles the cases with the small and the large number of similar transaction pairs separately and efficiently. Through experiments, we show that ROCKET achieves high-quality clustering with a dramatic performance improvement.
Woong-Kee LOH Yang-Sae MOON Jun-Gyu KANG
In this paper, we emphasize the need for data cleansing when clustering large-scale transaction databases and propose a new data cleansing method that improves clustering quality and performance. We evaluate our data cleansing method through a series of experiments. As a result, the clustering quality and performance were significantly improved by up to 165% and 330%, respectively.