Subspace clustering has attracted great attention due to its capability of finding salient patterns in high dimensional data. Order preserving subspace clusters have been proven to...
Image mining systems that can automatically extract semantically meaningful information (knowledge) from image data are increasingly in demand. The fundamental challenge in image m...
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
This paper proposes a generic framework for monitoring continuous spatial queries over moving objects. The framework distinguishes itself from existing work by being the first to ...
Co-location pattern discovery is to find classes of spatial objects that are frequently located together. For example, if two categories of businesses often locate together, they ...