Sciweavers

IDEAL
2000
Springer
13 years 8 months ago
A Note on Covariances for Categorical Data
Generalization of the covariance concept is discussed for mixed categorical and numerical data. Gini's definition of variance for categorical data gives us a starting point to...
Takashi Okada
VLDB
1998
ACM
204views Database» more  VLDB 1998»
13 years 9 months ago
Clustering Categorical Data: An Approach Based on Dynamical Systems
Wedescribea novel approachfor clustering collectionsof sets,andits applicationto theanalysis and mining of categoricaldata. By "categorical data," we meantableswith fiel...
David Gibson, Jon M. Kleinberg, Prabhakar Raghavan
PAKDD
2001
ACM
148views Data Mining» more  PAKDD 2001»
13 years 9 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...
PKDD
2005
Springer
117views Data Mining» more  PKDD 2005»
13 years 10 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...
EPIA
2005
Springer
13 years 10 months ago
An Extension of Self-organizing Maps to Categorical Data
Self-organizing maps (SOM) have been recognized as a powerful tool in data exploratoration, especially for the tasks of clustering on high dimensional data. However, clustering on ...
Ning Chen, Nuno C. Marques
SSDBM
2005
IEEE
218views Database» more  SSDBM 2005»
13 years 10 months ago
The "Best K" for Entropy-based Categorical Data Clustering
With the growing demand on cluster analysis for categorical data, a handful of categorical clustering algorithms have been developed. Surprisingly, to our knowledge, none has sati...
Keke Chen, Ling Liu
INFOVIS
2005
IEEE
13 years 10 months ago
Parallel Sets: Visual Analysis of Categorical Data
The discrete nature of categorical data makes it a particular challenge for visualization. Methods that work very well for continuous data are often hardly usable with categorical...
Fabian Bendix, Robert Kosara, Helwig Hauser
CIMCA
2005
IEEE
13 years 10 months ago
Modeling the Cross-Cultural Adaptation Process of Immigrants Using Categorical Data Clustering
— This paper introduces a quantitative method for social data analysis, which is based on the use of categorical data clustering. More specifically, we employ categorical data cl...
George E. Tsekouras
ICTAI
2007
IEEE
13 years 11 months ago
Conceptual Clustering Categorical Data with Uncertainty
Many real datasets have uncertain categorical attribute values that are only approximately measured or imputed. Uncertainty in categorical data is commonplace in many applications...
Yuni Xia, Bowei Xi
WSOM
2009
Springer
13 years 11 months ago
Career-Path Analysis Using Optimal Matching and Self-Organizing Maps
Abstract. This paper is devoted to the analysis of career paths and employability. The state-of-the-art on this topic is rather poor in methodologies. Some authors propose distance...
Sébastien Massoni, Madalina Olteanu, Patric...