Cluster analysis is the automated search for groups of related observations in a dataset.
Most clustering done in practice is based largely on heuristic but intuitively reasonable …

Living in the Information Age allows almost everyone have access to a large amount of
information and options to choose from in order to fulfill their needs. In many cases, the …

Finding the maximals in a collection of vectors is relevant to many applications. The maximal
set is related to the convex hull—and hence, linear optimization—and nearest neighbors …

This chapter surveys results in the design and analysis of self-organizing data structures for
the search problem. The general search problem in pointer data structures can be phrased …

We present a number of new results on one of the most extensively studied topics in
computational geometry, orthogonal range searching. All our results are in the standard …

MPEG-7 is the first international standard which contains a number of key techniques from
Computer Vision and Image Processing. The Curvature Scale Space technique was …

The maximal vector problem is to identify the maximals over a collection of vectors. This
arises in many contexts and, as such, has been well studied. The problem recently gained …

Many interesting search problems can be formulated as bi-objective search problems, that
is, search problems where two kinds of costs have to be minimized, for example, travel …

The skyline operator returns from a set of multi-dimensional objects a subset of superior
objects that are not dominated by others. This operation is considered very important in multi …

The skyline clause—also called the Pareto clause—recently has been proposed as an
extension to SQL. It selects the tuples that are Pareto optimal with respect to a set of …