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PAKDD
2007
ACM
158views Data Mining» more  PAKDD 2007»
16 years 17 days ago
Density-Sensitive Evolutionary Clustering
In this study, we propose a novel evolutionary algorithm-based clustering method, named density-sensitive evolutionary clustering (DSEC). In DSEC, each individual is a sequence of ...
Maoguo Gong, Licheng Jiao, Ling Wang, Liefeng Bo
ICDM
2003
IEEE
154views Data Mining» more  ICDM 2003»
15 years 11 months ago
MaPle: A Fast Algorithm for Maximal Pattern-based Clustering
Pattern-based clustering is important in many applications, such as DNA micro-array data analysis, automatic recommendation systems and target marketing systems. However, pattern-...
Jian Pei, Xiaoling Zhang, Moonjung Cho, Haixun Wan...
PSIVT
2009
Springer
139views Multimedia» more  PSIVT 2009»
15 years 11 months ago
Recovery Rate of Clustering Algorithms
This article provides a simple and general way for defining the recovery rate of clustering algorithms using a given family of old clusters for evaluating the performance of the a...
Fajie Li, Reinhard Klette
CIT
2007
Springer
16 years 19 days ago
Performance Assessment of Some Clustering Algorithms Based on a Fuzzy Granulation-Degranulation Criterion
In this paper a fuzzy quantization dequantization criterion is used to propose an evaluation technique to determine the appropriate clustering algorithm suitable for a particular ...
Sriparna Saha, Sanghamitra Bandyopadhyay
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 6 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu