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ICDM
2005
IEEE
138views Data Mining» more  ICDM 2005»
13 years 9 months ago
Labeling Unclustered Categorical Data into Clusters Based on the Important Attribute Values
Sampling has been recognized as an important technique to improve the efficiency of clustering. However, with sampling applied, those points which are not sampled will not have t...
Hung-Leng Chen, Kun-Ta Chuang, Ming-Syan Chen
IDA
2009
Springer
13 years 1 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
DAWAK
2004
Springer
13 years 9 months ago
Categorical Data Visualization and Clustering Using Subjective Factors
Clustering is an important data mining problem. However, most earlier work on clustering focused on numeric attributes which have a natural ordering to their attribute values. Rec...
Chia-Hui Chang, Zhi-Kai Ding
KDD
1999
ACM
166views Data Mining» more  KDD 1999»
13 years 8 months ago
CACTUS - Clustering Categorical Data Using Summaries
Clustering is an important data mining problem. Most of the earlier work on clustering focussed on numeric attributes which have a natural ordering on their attribute values. Rece...
Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishn...
EDBT
2004
ACM
192views Database» more  EDBT 2004»
14 years 3 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...