In this paper, we devise a method for the estimation of the true support of itemsets on data streams, with the objective to maximize one chosen criterion among {precision, recall}...
Pierre-Alain Laur, Richard Nock, Jean-Emile Sympho...
The primary constraint in the effective mining of data streams is the large volume of data which must be processed in real time. In many cases, it is desirable to store a summary...
We study clustering problems in the streaming model, where the goal is to cluster a set of points by making one pass (or a few passes) over the data using a small amount of storag...
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
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...