The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
In this paper, we will examine the problem of clustering massive domain data streams. Massive-domain data streams are those in which the number of possible domain values for each a...
We describe an annealing procedure that computes the normalized N-cut of a weighted graph G. The first phase transition computes the solution of the approximate normalized 2-cut p...
Spatial clustering, which groups similar spatial objects into classes, is an important research topic in spatial data mining. Many spatial clustering methods have been developed re...
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...