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Authors: Naoya Higuchi 1 ; Yasunobu Imamura 1 ; Tetsuji Kuboyama 2 ; Kouichi Hirata 1 and Takeshi Shinohara 1

Affiliations: 1 Kyushu Institute of Technology, Kawazu 680-4, Iizuka 820-8502 and Japan ; 2 Gakushuin University, Mejiro 1-5-1, Toshima, Tokyo 171-8588 and Japan

ISBN: 978-989-758-351-3

Keyword(s): Similarity Search, Sketch, Ball Partitioning, Hamming Distance, Dimension Reduction, Distance Lower Bound.

Abstract: We discuss the nearest neighbor search using sketch which is a kind of locality sensitive hash (LSH). Nearest neighbor search using sketch is done in two stages. In the first stage, the top K candidates, which have close sketches to a query, are selected, where K ≥ 1. In the second stage, the nearest object to the query from K candidates is selected by performing actual distance calculations. Conventionally, higher accurate search requires wider sketches than 32-bit. In this paper, we propose search methods using narrow 16-bit sketch, which enables efficient data management by buckets and implement a faster first stage. To keep accuracy, search using 16-bit sketch requires larger K than using 32-bit sketch. By sorting the data objects according to sketch’s values, cost influence due to the increase in the number of candidates K can be reduced by improving memory locality in the second stage search. The proposed method achieves about 10 times faster search speed while maintaining accur acy. (More)

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Paper citation in several formats:
Higuchi, N.; Imamura, Y.; Kuboyama, T.; Hirata, K. and Shinohara, T. (2019). Fast Nearest Neighbor Search with Narrow 16-bit Sketch.In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-351-3, pages 540-547. DOI: 10.5220/0007377705400547

@conference{icpram19,
author={Naoya Higuchi. and Yasunobu Imamura. and Tetsuji Kuboyama. and Kouichi Hirata. and Takeshi Shinohara.},
title={Fast Nearest Neighbor Search with Narrow 16-bit Sketch},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2019},
pages={540-547},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007377705400547},
isbn={978-989-758-351-3},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Fast Nearest Neighbor Search with Narrow 16-bit Sketch
SN - 978-989-758-351-3
AU - Higuchi, N.
AU - Imamura, Y.
AU - Kuboyama, T.
AU - Hirata, K.
AU - Shinohara, T.
PY - 2019
SP - 540
EP - 547
DO - 10.5220/0007377705400547

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