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PAKDD
2007
ACM
158views Data Mining» more  PAKDD 2007»
14 years 2 months 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»
14 years 1 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»
14 years 13 days 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
14 years 2 months 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»
14 years 8 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