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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
Publication Date: 2011/10/01
Online ISSN: 1745-1361
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.