Abstract In data clustering, many approaches have been proposed. For example, K-means method and hierarchical method. A problem is in effect by initial value and criterion to comb...
Abstract. We present a clustering method for continuous data. It defines local clusters into the (primary) data space but derives its similarity measure from the posterior distribu...
In this paper, we initiate a theoretical study of the problem of clustering data under interactive feedback. We introduce a query-based model in which users can provide feedback to...
We present an online adaptive clustering algorithm in a decision tree framework which has an adaptive tree and a code formation layer. The code formation layer stores the represen...
Estimating the optimal number of clusters for a dataset is one of the most essential issues in cluster analysis. An improper pre-selection for the number of clusters might easily ...