— In this paper, we investigate the problem of grouping the sensor nodes into clusters to enhance the overall scalability of the network. A selected set of nodes, known as gatewa...
The segmentation of time-series is a constrained clustering problem: the data points should be grouped by their similarity, but with the constraint that all points in a cluster mus...
Low-frequency variability in geopotential height records of the Northern Hemisphere is a topic of significance in atmospheric science, having profound implications for climate mod...
Padhraic Smyth, Michael Ghil, Kayo Ide, Joseph Rod...
We propose a scalable technique called Seeded Clustering that allows us to maintain R-tree indices by bulk insertion while keeping pace with high data arrival rates. Our approach ...
Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...