The discovery and construction of inherent regions in large spatial datasets is an important task for many research domains such as climate zoning, eco-region analysis, public heal...
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
Coclustering heterogeneous data has attracted extensive attention recently due to its high impact on various important applications, such us text mining, image retrieval, and bioin...
We examine the problem of monitoring and identification of correlated burst patterns in multi-stream time series databases. Our methodology is comprised of two steps: a burst dete...
We propose a shape analysis that adapts to some of the complex composite data structures found in industrial systems-level programs. Examples of such data structures include “cyc...