Many applications in wireless sensor networks (WSNs) benefit significantly from organizing nodes into groups, called clusters, because data aggregation and data filtering applied i...
This paper centers on the discussion of k-medoid-style clustering algorithms for supervised summary generation. This task requires clustering techniques that identify class-unifor...
Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because ...
Abstract. Finding correlation clusters in the arbitrary subspaces of highdimensional data is an important and a challenging research problem. The current state-of-the-art correlati...
- Clustering of data is an important data mining application. One of the problems with traditional partitioning clustering methods is that they partition the data into hard bound n...