Common linkage procedures that make use of different

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Unformatted text preview: nt is member of exactly one cluster. One determines the similarity between the clusters on the basis of this first clustering and selects the two clusters p, q of the clustering P with the minimum distance dist( p, q). Both cluster are merged and one receives a new clustering. One continues this procedure and re-calculates the distances between the new clusters in order to join again the two clusters with the minimum distance dist( p, q). The algorithm stops if only one cluster is remaining. The distance can be computed according to Eq. 4. It is also possible to derive the clusters directly on the basis of the similarity relationship given by a matrix. For the computation of the similarity between clusters that contain more than one element different distance measures for clusters can be used, e.g. based Hierarchical Clustering Algorithms 40 LDV-FORUM A Brief Survey of Text Mining on the outer cluster shape or the cluster center. Common linkage procedures that make use of different cluster distance measures are single linkage, average linkage or Ward’s procedure. The obtained clustering depends on the used measure. Details can be found, for example,...
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This note was uploaded on 06/19/2011 for the course IT 2258 taught by Professor Aymenali during the Summer '11 term at Abu Dhabi University.

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