Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
— We present a solution to the problem of identifying clusters from MIMO measurement data in a data window, with a minimum of user interaction. Conventionally, visual inspection ...
Nicolai Czink, Pierluigi Cera, Jari Salo, Ernst Bo...
In previous work, we have proposed a novel approach to data clustering based on the explicit optimization of a partitioning with respect to two complementary clustering objectives ...
In this paper, we propose a novel document clustering method based on the non-negative factorization of the termdocument matrix of the given document corpus. In the latent semanti...