In this paper we propose a method for grouping and summarizing large sets of association rules according to the items contained in each rule. We use hierarchical clustering to par...
A data set can be clustered in many ways depending on the clustering algorithm employed, parameter settings used and other factors. Can multiple clusterings be combined so that th...
Alexander P. Topchy, Anil K. Jain, William F. Punc...
Computing a suitable measure of consensus among several clusterings on the same data is an important problem that arises in several areas such as computational biology and data mi...
Piotr Berman, Bhaskar DasGupta, Ming-Yang Kao, Jie...
With the proliferation of multimedia data, there is increasing need to support the indexing and searching of high dimensional data. Recently, a vector approximation based techniqu...
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...