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SDM
2007
SIAM
184views Data Mining» more  SDM 2007»
15 years 4 months ago
Mining Naturally Smooth Evolution of Clusters from Dynamic Data
Many clustering algorithms have been proposed to partition a set of static data points into groups. In this paper, we consider an evolutionary clustering problem where the input d...
Yi Wang, Shi-Xia Liu, Jianhua Feng, Lizhu Zhou
SIGIR
2003
ACM
15 years 8 months ago
ReCoM: reinforcement clustering of multi-type interrelated data objects
Most existing clustering algorithms cluster highly related data objects such as Web pages and Web users separately. The interrelation among different types of data objects is eith...
Jidong Wang, Hua-Jun Zeng, Zheng Chen, Hongjun Lu,...
BMCBI
2008
142views more  BMCBI 2008»
15 years 3 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
JDCTA
2010
134views more  JDCTA 2010»
14 years 10 months ago
A New Clustering Segmentation Algorithm of 3D Medical Data Field Based on Data Mining
Direct 3D volume segmentation is one of the difficult and hot research fields in 3D medical data field processing. Using the clustering and analyzing techniques of data mining, a ...
Li Xinwu
142
Voted
BMCBI
2008
122views more  BMCBI 2008»
15 years 3 months ago
A practical comparison of two K-Means clustering algorithms
Background: Data clustering is a powerful technique for identifying data with similar characteristics, such as genes with similar expression patterns. However, not all implementat...
Gregory A. Wilkin, Xiuzhen Huang