Clustering is an important data mining problem. However, most earlier work on clustering focused on numeric attributes which have a natural ordering to their attribute values. Rec...
Hierarchical conceptual clustering has been proven to be a useful data mining technique. Graph-based representation of structural information has been shown to be successful in kn...
A split-and-merge framework based on a maximum variance criterion is proposed for disparity clustering. The proposed algorithm transforms low-level stereo disparity information to...
Since a large number of clustering algorithms exist, aggregating different clustered partitions into a single consolidated one to obtain better results has become an important pro...
Clusters of PC containing mostly general purpose hardware have become more and more usable for high performance computing tasks in the past few years. Clustering existing systems ...