Numerous mesh algorithms such as parametrization, radiosity, and collision detection require the decomposition of meshes into a series of clusters. In this paper we present two no...
We explore in this paper the efficient clustering of item data. Different from those of the traditional data, the features of item data are known to be of high dimensionality and...
Forming consensus clusters from multiple input clusterings can improve accuracy and robustness. Current clustering ensemble methods require specifying the number of consensus clust...
Pu Wang, Carlotta Domeniconi, Kathryn Blackmond La...
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
The detection of correlations between different features in high dimensional data sets is a very important data mining task. These correlations can be arbitrarily complex: One or...