In this paper, a statistical clustering model and algorithm have been discussed. Finding the optimal solution to clustering problem is transformed into simulating the equilibrium ...
Hierarchical clustering methods are important in many data mining and pattern recognition tasks. In this paper we present an efficient coarse grained parallel algorithm for Single...
Monitoring cluster evolution in data streams is a major research topic in data streams mining. Previous clustering methods for evolving data streams focus on global clustering res...
Liang Tang, Chang-jie Tang, Lei Duan, Chuan Li, Ye...
Internet-based clusters of workstations have been extensively used to execute parallel applications. Although these internet-based clusters seem to be an easy and inexpensive way ...
—The conventional K-Means clustering algorithm must know the number of clusters in advance and the clustering result is sensitive to the selection of the initial cluster centroid...
Jing Xiao, YuPing Yan, Ying Lin, Ling Yuan, Jun Zh...