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Fast indexing method for multidimensional nearest-neighbor search

This paper describes a snapshot of work in progress on the development of an efficient file-access method for similarity searching in high-dimensional vector spaces. This method has applications in image databases, where images are accessed via high-dimensional feature vectors, as well as other areas. The technique is based on using a collection of space-filling curves, as an auxiliary indexing structure. Initial performance analyses suggest that the method works as efficiently in moderately high-dimensional spaces (256 dimensions), with tolerable storage and execution-time overhead.