Conference Themes
Researchers interested in classification, clustering, data analysis, multivariate analysis and computational statistics and their applications are invited to participate.

Classification Theory
     T1.      Fuzzy Methods
     T2.      Hierarchical Classification
     T3.      Non Hierarchical Classification
     T4.     
Pattern Recognition
     T5
.     
Bayesian Classification
     T6
.     
Classification of Multiway and Functional Data
    
T7.      Probabilistic Methods for Clustering
    
T8.      Consensus of Classifications
    
T9.      Spatial Clustering
  
T10.      Validity of Clustering
  
T11.      Neural Networks and Machine Learning Methods for Classification
  
T12.      Genetic Algorithms
  
T13.      Classification with Constraints
  
T14.      Mixture and Latent Class Models for Clustering.

Multivariate Data Analysis
   
D1.      Categorical Data Analysis
    D2.      Correspondence Analysis
    D3.      Biplots
    D4.      Factor Analysis and Dimension Reduction Methods
    D5.      Discrimination and Classification
    D6.      Multiway Methods
    D7.      Symbolic Data Analysis
    D8.      Non Linear Data Analysis
    D9.      Bayesian Multivariate Analysis
  D10.      Multilevel Analysis
  D11.      Covariance Structure Analysis
  D12.      Partial Least Squares
  D13.      Regression and Classification Trees
  D14.      Robust Methods and Data Diagnostics
  D15.      Spatial Data Analysis
  D16.      Graphical Methods
  D17.      Nonparametric and Semiparametric Regression
 
D18.      Data Mining.

Proximity Structure Analysis
     P1.      Multidimensional Scaling
     P2.      Similarities and Dissimilarities
     P3.      Unfolding and Other Special Scaling Methods
     P4.      Multiway Scaling.

Software Developments
    S1.      Algorithms for Classification
    S2.      Data Visualization
    S3.      Algorithms for Multivariate Data Analysis.

Applied Classification and Data Analysis
    A1.      Classification of Textual Data
    A2.      Data Analysis in Economics and Finance
    A3.      Data Analysis in Environmental Sciences
    A4.      Classification in Medical Science
    A5.      Cognitive Sciences and Classification
    A6.      Classification in Biology and Ecology
    A7.      Data Analysis in Demography
    A8.      Classification of Microarray Data
    A9.      Data Analysis for Customer Satisfaction and Service Quality Evaluation
   A10.      Applications of Data and Web Mining.