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Index Structures for Fast Similarity Search for Binary Vectors

  • NEW MEANS OF CYBERNETICS, INFORMATICS, COMPUTER ENGINEERING, AND SYSTEMS ANALYSIS
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Abstract

This article reviews index structures for fast similarity search for objects represented by binary vectors (with components equal to 0 or 1). Structures for both exact and approximate search by Hamming distance and other similarity measures are considered. Mainly, index structures are presented that are based on hash tables and similarity-preserving hashing and also on tree structures, neighborhood graphs, and distributed neural autoassociative memory. Ideas of well-known algorithms and algorithms proposed in recent years are stated.

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Authors and Affiliations

  1. International Scientific-Educational Center of Information Technologies and Systems, NAS of Ukraine and MES of Ukraine, Kyiv, Ukraine

    D. A. Rachkovskij

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  1. D. A. Rachkovskij
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Correspondence to D. A. Rachkovskij.

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Translated from Kibernetika i Sistemnyi Analiz, No. 5, September–October, 2017, pp. 167–192.

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Rachkovskij, D.A. Index Structures for Fast Similarity Search for Binary Vectors. Cybern Syst Anal 53, 799–820 (2017). https://doi.org/10.1007/s10559-017-9983-x

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