The problem of searching the elements of a set that are close to a given query element
under some similarity criterion has a vast number of applications in many branches of …

Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …

The problem of inducing, learning or inferring grammars has been studied for decades, but
only in recent years has grammatical inference emerged as an independent field with …

The area of similarity searching is a very hot topic for both research and c-mercial
applications. Current data processing applications use data with c-siderably less structure …

Spatio-temporal trajectory analytics are useful in diversified applications such as urban
planning, infrastructure development, and vehicular networks. Trajectory similarity measure …

Similarity search is a very important operation in multimedia databases and other database
applications involving complex objects, and involves finding objects in a data set S similar to …

We propose a new data structure to search in metric spaces. A metric space is formed by a
collection of objects and a distance function defined among them which satisfies the triangle …

The problem of finding the closest point in high-dimensional spaces is common in pattern
recognition. Unfortunately, the complexity of most existing search algorithms, such as kd tree …

Given a set S of points in a metric space with distance function D, the nearest-neighbor
searching problem is to build a data structure for S so that for an input query point q, the …

With few exceptions, proximity search algorithms in metric spaces based on the use of pivots
select them at random among the objects of the metric space. However, it is well known that …