Nearest Neighbor Search using Sketches as Quantized Images of Dimension Reduction

Naoya Higuchi, Yasunobu Imamura, Tetsuji Kuboyama, Kouichi Hirata, Takeshi Shinohara

Abstract

In this paper, we discuss sketches based on ball partitioning (BP), which are compact bit sequences representing multidimensional data. The conventional nearest search using sketches consists of two stages. The first stage selects candidates depending on the Hamming distances between sketches. Then, the second stage selects the nearest neighbor from the candidates. Since the Hamming distance cannot completely reflect the original distance, more candidates are needed to achieve higher accuracy. On the other hand, we can regard BP sketches as quantized images of a dimension reduction. Although quantization error is very large if we use only sketches to compute distances, we can partly recover distance information using query. That is, we can compute a lower bound of distance between a query and a data using only query and the sketch of the data. We propose candidate selection methods at the first stage using the lower bounds. Using the proposed method, higher level of accuracy for nearest neighbor search is shown through experimenting on multidimensional data such as images, music and colors.

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Paper Citation


in Harvard Style

Higuchi N., Imamura Y., Kuboyama T., Hirata K. and Shinohara T. (2018). Nearest Neighbor Search using Sketches as Quantized Images of Dimension Reduction.In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-276-9, pages 356-363. DOI: 10.5220/0006585003560363


in Bibtex Style

@conference{icpram18,
author={Naoya Higuchi and Yasunobu Imamura and Tetsuji Kuboyama and Kouichi Hirata and Takeshi Shinohara},
title={Nearest Neighbor Search using Sketches as Quantized Images of Dimension Reduction},
booktitle={Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2018},
pages={356-363},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006585003560363},
isbn={978-989-758-276-9},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Nearest Neighbor Search using Sketches as Quantized Images of Dimension Reduction
SN - 978-989-758-276-9
AU - Higuchi N.
AU - Imamura Y.
AU - Kuboyama T.
AU - Hirata K.
AU - Shinohara T.
PY - 2018
SP - 356
EP - 363
DO - 10.5220/0006585003560363