Distinct Clustering techniques make diverse assumptions over the construction from the data, normally described by some similarity metric and evaluated, one example is, by interior compactness, or maybe the similarity between users of precisely the same cluster, and separation, the distinction between clusters. Other procedures are according to estimated density http://emjun.com/index.php?mid=mmm&document_srl=1250534