ROCKET: A Robust Parallel Algorithm for Clustering Large-Scale Transaction Databases

Woong-Kee LOH  Yang-Sae MOON  Heejune AHN  

IEICE TRANSACTIONS on Information and Systems   Vol.E94-D   No.10   pp.2048-2051
Publication Date: 2011/10/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E94.D.2048
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Artificial Intelligence, Data Mining
divisive hierarchical clustering,  large-scale transaction databases,  parallelization,  

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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.