Hybrid Hierarchical Clustering: an Experimental Analysis
نویسندگان
چکیده
In this paper, we present a hybrid clustering method that combines the divisive hierarchical clustering with the agglomerative hierarchical clustering. We used the bisect K-means divisive clustering algorithm in our method. First, we cluster the document collection using bisect K-means clustering algorithm with K’ > K as the total number of clusters. Second, we calculate the centroids of K’ clusters obtained from the previous step. Then we apply the Unweighted Pair Group Method with Arithmetic Mean (UPGMA) agglomerative hierarchical algorithm on these centroids for the given K. After the UPGMA finds K clusters in these K’ centroids, if two centroids ended up in the same cluster, then all of their documents will belong to the same cluster. ∗ c © University of Kentucky, 2011.
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