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Comparison of two fast nearest-neighbour search methods in high-dimensional large-sized databases

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2004) 3138 868-875
DOI: 10.1007/978-3-540-27868-9_95
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Abstract

In this paper we show the results of a performance comparison between two Nearest Neighbour Search Methods: one, proposed by Arya & Mount, is based on a kd-tree data structure and a Branch and Bound approximate search algorithm [1], and the other is a search method based on dimensionality projections, presented by Nene & Nayar in [5]. A number of experiments have been carried out in order to find the best choice to work with high dimensional points and large data sets. © Springer-Verlag 2004.

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APA

Cano, J., Pérez-Cortés, J. C., & Salvador, I. (2004). Comparison of two fast nearest-neighbour search methods in high-dimensional large-sized databases. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3138, 868–875. https://doi.org/10.1007/978-3-540-27868-9_95

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