Central and subspace clustering methods are at the core of many segmentation problems in computer vision. However, both methods fail to give the correct segmentation in many pract...
This paper investigates the applicability of distributed clustering technique, called RACHET [1], to organize large sets of distributed text data. Although the authors of RACHET c...
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...
: Clustering provides an effective mechanism for energy-efficient data delivery in wireless sensor networks. To reduce communication cost, most clustering algorithms rely on a sens...
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...