Existing density-based data stream clustering algorithms use a two-phase scheme approach consisting of an online phase, in which raw data is processed to gather summary statistics...
Agostino Forestiero, Clara Pizzuti, Giandomenico S...
This paper proposes a novel data clustering algorithm, coined ‘cellular ants’, which combines principles of cellular automata and ant colony optimization algorithms to group s...
We propose a new class of consistency constraints for Linear Programming (LP) relaxations for finding the most probable (MAP) configuration in graphical models. Usual cluster-base...
Nonnegative Matrix Factorization (NMF) has been proven to be effective in text mining. However, since NMF is a well-known unsupervised components analysis technique, the existing ...
Clustering algorithms are intensively used in the image analysis field in compression, segmentation, recognition and other tasks. In this work we present a new approach in clusteri...