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PAKDD
2001
ACM
148views Data Mining» more  PAKDD 2001»
13 years 11 months ago
Scalable Hierarchical Clustering Method for Sequences of Categorical Values
Data clustering methods have many applications in the area of data mining. Traditional clustering algorithms deal with quantitative or categorical data points. However, there exist...
Tadeusz Morzy, Marek Wojciechowski, Maciej Zakrzew...
EDBT
2004
ACM
192views Database» more  EDBT 2004»
14 years 7 months ago
LIMBO: Scalable Clustering of Categorical Data
Abstract. Clustering is a problem of great practical importance in numerous applications. The problem of clustering becomes more challenging when the data is categorical, that is, ...
Periklis Andritsos, Panayiotis Tsaparas, Ren&eacut...
IDA
2009
Springer
13 years 5 months ago
Context-Based Distance Learning for Categorical Data Clustering
Abstract. Clustering data described by categorical attributes is a challenging task in data mining applications. Unlike numerical attributes, it is difficult to define a distance b...
Dino Ienco, Ruggero G. Pensa, Rosa Meo
BMCBI
2004
113views more  BMCBI 2004»
13 years 7 months ago
Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering
Background: Microarray technologies produced large amount of data. The hierarchical clustering is commonly used to identify clusters of co-expressed genes. However, microarray dat...
Alexandre G. de Brevern, Serge A. Hazout, Alain Ma...
ICDE
1999
IEEE
183views Database» more  ICDE 1999»
14 years 8 months ago
ROCK: A Robust Clustering Algorithm for Categorical Attributes
Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
Sudipto Guha, Rajeev Rastogi, Kyuseok Shim