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    STUDIA INFORMATICA - Issue no. 2 / 2005  
         
  Article:   ADAPTIVE CLUSTERING USING A CORE-BASED APPROACH.

Authors:  GABRIELA ŞERBAN, ALINA CÂMPAN. 		 
       
         
  Abstract:  This paper studies an adaptive clustering problem. We focus on re-clustering an object set, previously clustered, when the feature set char- acterizing the objects increases. We propose an adaptive, k-means based clustering method, Core Based Adaptive k-means (CBAk), that adjusts the partitioning into clusters that was established by applying k-means or CBAk before the feature set changed. We aim to reach the result more eficiently than running k-means starting from the current clustering. Experiments test- ing the method''s eficiency are also reported.  
         
     
         
         
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