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    STUDIA INFORMATICA - Issue no. 1 / 2006  
         
  Article:   A COMPARISON OF CLUSTERING TECHNIQUES IN ASPECT MINING.

Authors:  GABRIELA ŞERBAN, GRIGORETA SOFIA MOLDOVAN.
 
       
         
  Abstract:  This paper aims at presenting and comparing three clustering algorithms in aspect mining: k-means (KM), fuzzy c-means (FCM) and hi- erarchical agglomerative clustering (HAC). Clustering is used in order to identify crosscutting concerns. We propose some quality measures in order to evaluate the results and we comparatively analyze the obtained results on two case studies.  
         
     
         
         
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