On subspace clustering with density consciousness

Authors:
Yi-Hong Chu;Jen-Wei Huang;Kun-Ta Chuang;Ming-Syan Chen
Affiliations:
National Taiwan University, Taipei, Taiwan, ROC;National Taiwan University, Taipei, Taiwan, ROC;National Taiwan University, Taipei, Taiwan, ROC;National Taiwan University, Taipei, Taiwan, ROC
Venue:
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Year:
2006

Citing 3
Cited 0

Automatic subspace clustering of high dimensional data for data mining applications

SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Entropy-based subspace clustering for mining numerical data

KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent patterns without candidate generation

SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a problem, called "the density divergence problem" is explored. This problem is related to the phenomenon that the densities of the clusters vary in different subspace cardinalities. We take the densities into consideration in subspace clustering and explore an algorithm to adaptively determine different density thresholds to discover clusters in different subspace cardinalities.