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KDD
1999
ACM
166views Data Mining» more  KDD 1999»
13 years 12 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...
PKDD
2005
Springer
117views Data Mining» more  PKDD 2005»
14 years 1 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...
DAWAK
2004
Springer
14 years 1 months ago
SCLOPE: An Algorithm for Clustering Data Streams of Categorical Attributes
Clustering is a difficult problem especially when we consider the task in the context of a data stream of categorical attributes. In this paper, we propose SCLOPE, a novel algorith...
Kok-Leong Ong, Wenyuan Li, Wee Keong Ng, Ee-Peng L...
IJDMB
2006
125views more  IJDMB 2006»
13 years 7 months ago
Bi-level clustering of mixed categorical and numerical biomedical data
: Biomedical data sets often have mixed categorical and numerical types, where the former represent semantic information on the objects and the latter represent experimental result...
Bill Andreopoulos, Aijun An, Xiaogang Wang
FSS
2008
130views more  FSS 2008»
13 years 7 months ago
A fuzzy k-partitions model for categorical data and its comparison to the GoM model
The grade of membership (GoM) model uses fuzzy sets as memberships of each individual to extreme profiles (or classes) on the likelihood function of multivariate multinomial distr...
Miin-Shen Yang, Yu-Hsuan Chiang, Chiu-Chi Chen, Ch...