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Clustering ensemble performance is affected by two main factors: diversity and quality. Selection of a subset of available ensemble members based on diversity and quality often leads to a more accurate ensemble solution. However, there is not a certain relationship between diversity and quality in selection of subset of ensemble members. This paper proposes the Hierarchical Cluster Ensemble Selection (HCES) method and diversity measure to explore how diversity and quality affect final results. The HCES uses single-link, average-link, and complete link agglomerative clustering methods for the selection of ensemble members hierarchically. A pair-wise diversity measure from the recent literature and the proposed diversity measure are applied to these agglomerative clustering algorithms. Using the proposed diversity measure in HCES leads to more diverse ensemble members than that of pairwise diversity …