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Clustering Methods for Symbolic Objects

  • Marie Chavent
  • Hans-Hermann Bock
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

One of the most common tasks in (classical as well as symbolic) data analysis is the detection and construction of ‘homogeneous’ groups C1, C2,… of objects in a population Ω or E such that objects from the same group show a high similarity whereas objects from different groups are typically more dissimilar. Such groups are usually called ‘clusters’ and must be constructed on the basis of the (classical or symbolic) data which were recorded for the objects.

Keywords

Dissimilarity Measure Symbolic Data Beef Tallow Galois Connection Generality Degree 
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

  • Marie Chavent
    • 1
    • 2
  • Hans-Hermann Bock
    • 3
  1. 1.INRIA-RocquencourtLe ChesnayFrance
  2. 2.LISE-CEREMADEUniversité Paris IX — DauphineFrance
  3. 3.Institut für StatistikRWTH AachenGermany

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