Abstract. The Evolutionary Geometric Near-neighbor Access Tree (EGNAT) is a recently proposed data structure that is suitable for indexing large collections of complex objects. It ...
In this paper we show how the complexity of performing nearest neighbor (NNS) search on a metric space is related to the expansion of the metric space. Given a metric space we loo...
Abstract. Searching in metric spaces is a very active field since it offers methods for indexing and searching by similarity in collections of unstructured data. These methods sele...
Metric access methods (MAMs), such as the M-tree, are powerful index structures for supporting ty queries on metric spaces, which represent a common abstraction for those searchin...
A number of problems in computer science can be solved efficiently with the so called memory based or kernel methods. Among this problems (relevant to the AI community) are multime...