Similarity Search in High-Dimensional Vector Spaces

This dissertation addresses the problem of identifying the most similar objects in a database given a set of reference objects and a set of features. It investigates the so-called "Curse of Dimensionality", and presents an organization for NN-Search ("Nearest Neighbour Search") optimized for high-dimensional spaces - the so-called "Vector Approximation File" (VA-File). The text shows the superiority of the VA-File theoretically and through experiments. The VA-File is also discussed with reference to approximate search and parallel search in a cluster of workstations. This dissertaion also provides an indexing technique that allows for interactive-time similarity search even in huge databases.