From: pfeiffer@igi.tugraz.at   
      
   Sengly wrote:   
   > Dear all,   
   >   
   > I would like you to share with me your experience on how should I   
   > handle my data. I have 1000 objects and I have a list of pair   
   > similarity of them. I would like to know how to cluster them into   
   > different groups according to their similarity?   
   >   
   > I have browse through various methods such as hierarchy, k-means,   
   > scaling dimension, etc. I really like k-means method but the problem   
   > is that I don't have points (and their coordinates) in space but   
   > rather their similarity.   
      
   Affinity propagation is a really good suggestion. A simple alternative   
   is to use variants of the k-medoids algorithm, which is similar to   
   k-means, but needs only the distances, not points or coordinates.   
      
   Regards, Michael   
      
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