Symbolic Data Analysis and the SODAS Project: Purpose, History, Perspective

  • Edwin Diday
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


In many domains of human activities it is now quite common to record huge sets of data in large data bases. It becomes a task of first importance to summarize these data in terms of their underlying concepts in order to extract new knowledge from them. These concepts can only be described by more complex type of data which we call symbolic data as they contain internal variation and they are structured. In this context, we have a rapidly increasing need to extend standard data analysis methods (exploratory, graphical representations, clustering, factorial analysis, discrimination,…) to these symbolic data.


Symbolic Data Factorial Axis Symbolic Variable Symbolic Description Individual Description 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Edwin Diday
    • 1
  1. 1.LISE-CEREMADEUniversité Paris IX — DauphineFrance

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