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PKDD
2005
Springer
117views Data Mining» more  PKDD 2005»
15 years 12 months ago
A Bi-clustering Framework for Categorical Data
Bi-clustering is a promising conceptual clustering approach. Within categorical data, it provides a collection of (possibly overlapping) bi-clusters, i.e., linked clusters for both...
Ruggero G. Pensa, Céline Robardet, Jean-Fra...
JBI
2006
107views Bioinformatics» more  JBI 2006»
15 years 6 months ago
Knowledge guided analysis of microarray data
To microarray expression data analysis, it is well accepted that biological knowledge-guided clustering techniques show more advantages than pure mathematical techniques. In this ...
Zhuo Fang, Jiong Yang, Yixue Li, Qing-ming Luo, Le...
SIGMOD
1998
ACM
99views Database» more  SIGMOD 1998»
15 years 10 months ago
CURE: An Efficient Clustering Algorithm for Large Databases
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...
Sudipto Guha, Rajeev Rastogi, Kyuseok Shim
AUSDM
2008
Springer
212views Data Mining» more  AUSDM 2008»
15 years 8 months ago
Clustering and Classification of Maintenance Logs using Text Data Mining
Spreadsheets applications allow data to be stored with low development overheads, but also with low data quality. Reporting on data from such sources is difficult using traditiona...
Brett Edwards, Michael Zatorsky, Richi Nayak
IMSCCS
2007
IEEE
16 years 24 days ago
Linear Correlation Analysis of Numeric Attributes for Government Data
To analyze the linear correlations of numeric attributes of government data, this paper proposes a method based on the clustering algorithm. A clustering method is adopted to prun...
Ying Chen, Guochang Gu, Tian-yang Lv, Shaobin Huan...