research-article

Selective Hashing: Closing the Gap between Radius Search and k-NN Search

Authors:

Sheng WangAuthors Info & Claims

KDD '15: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Pages 349 - 358

https://doi.org/10.1145/2783258.2783284

Published: 10 August 2015 Publication History

Abstract

Locality Sensitive Hashing (LSH) and its variants, are generally believed to be the most effective radius search methods in high-dimensional spaces. However, many applications involve finding the k nearest neighbors (k-NN), where the k-NN distances of different query points may differ greatly and the performance of LSH suffers. We propose a novel indexing scheme called Selective Hashing, where a disjoint set of indices are built with different granularities and each point is only stored in the most effective index. Theoretically, we show that k-NN search using selective hashing can achieve the same recall as a fixed radius LSH search, using a radius equal to the distance of the c₁k_th nearest neighbor, with at most c₂ times overhead, where c₁ and c₂ are small constants. Selective hashing is also easy to build and update, and outperforms all the state-of-the-art algorithms such as DSH and IsoHash.

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Cited By

Jiang YFang YMa CCao XLi C(2022)Effective community search over large star-schema heterogeneous information networksProceedings of the VLDB Endowment10.14778/3551793.355179515:11(2307-2320)Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.14778/3551793.3551795
Yu TLiu JYang YLi YFei HLi PZhang ARangwala H(2022)EGM: Enhanced Graph-based Model for Large-scale Video Advertisement SearchProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3534678.3539061(4443-4451)Online publication date: 14-Aug-2022
https://dl.acm.org/doi/10.1145/3534678.3539061
Guo CLiu WLiu XZhang Y(2022)Secure Similarity Search Over Encrypted Non-Uniform DatasetsIEEE Transactions on Cloud Computing10.1109/TCC.2020.300023310:3(2102-2117)Online publication date: 1-Jul-2022
https://doi.org/10.1109/TCC.2020.3000233
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Index Terms

Selective Hashing: Closing the Gap between Radius Search and k-NN Search
1. Information systems
  1. Information storage systems
    1. Record storage systems
      1. Record storage alternatives
        Hashed file organization
2. Theory of computation
  1. Design and analysis of algorithms

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cover image ACM Conferences

KDD '15: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 2015

2378 pages

ISBN:9781450336642

DOI:10.1145/2783258

General Chairs:
Longbing Cao
University of Technology, Sydney
,
Chengqi Zhang
University of Technology, Sydney
,
Program Chairs:
Thorsten Joachims
Cornell University
,
Geoff Webb
Monash University
,
Dragos D. Margineantu
Boeing Research
,
Graham Williams
Australian Taxation Office

Copyright © 2015 ACM.

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Published: 10 August 2015

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National Research Foundation Prime Minister's Office Singapore
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KDD '15

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KDD '15: The 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 10 - 13, 2015

NSW, Sydney, Australia

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KDD '15 Paper Acceptance Rate 160 of 819 submissions, 20%;

Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

Jiang YFang YMa CCao XLi C(2022)Effective community search over large star-schema heterogeneous information networksProceedings of the VLDB Endowment10.14778/3551793.355179515:11(2307-2320)Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.14778/3551793.3551795
Yu TLiu JYang YLi YFei HLi PZhang ARangwala H(2022)EGM: Enhanced Graph-based Model for Large-scale Video Advertisement SearchProceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3534678.3539061(4443-4451)Online publication date: 14-Aug-2022
https://dl.acm.org/doi/10.1145/3534678.3539061
Guo CLiu WLiu XZhang Y(2022)Secure Similarity Search Over Encrypted Non-Uniform DatasetsIEEE Transactions on Cloud Computing10.1109/TCC.2020.300023310:3(2102-2117)Online publication date: 1-Jul-2022
https://doi.org/10.1109/TCC.2020.3000233
Ding JLiu ZZhang YGong SYu G(2022)LayerLSH: Rebuilding Locality-Sensitive Hashing Indices by Exploring Density of Hash ValuesIEEE Access10.1109/ACCESS.2022.318280210(69851-69865)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3182802
Kim HMin SPark KLin XHong SHan W(2020)IDARProceedings of the VLDB Endowment10.14778/3397230.339724113:9(1456-1468)Online publication date: 26-Jun-2020
https://dl.acm.org/doi/10.14778/3397230.3397241
Lu KWang HWang WKudo M(2020)VHPProceedings of the VLDB Endowment10.14778/3397230.339724013:9(1443-1455)Online publication date: 1-May-2020
https://dl.acm.org/doi/10.14778/3397230.3397240
Li CZhang MAndersen DHe YMaier DPottinger RDoan ATan WAlawini ANgo H(2020)Improving Approximate Nearest Neighbor Search through Learned Adaptive Early TerminationProceedings of the 2020 ACM SIGMOD International Conference on Management of Data10.1145/3318464.3380600(2539-2554)Online publication date: 11-Jun-2020
https://dl.acm.org/doi/10.1145/3318464.3380600
Eghbali SAshtiani HTahvildari L(2020)Online Nearest Neighbor Search Using Hamming Weight TreesIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2019.290239142:7(1729-1740)Online publication date: 1-Jul-2020
https://doi.org/10.1109/TPAMI.2019.2902391
Li WZhang YSun YWang WLi MZhang WLin X(2020)Approximate Nearest Neighbor Search on High Dimensional Data — Experiments, Analyses, and ImprovementIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2019.290920432:8(1475-1488)Online publication date: 1-Aug-2020
https://doi.org/10.1109/TKDE.2019.2909204
Ouni A(2020)A machine learning approach for image retrieval tasks2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ)10.1109/IVCNZ51579.2020.9290617(1-5)Online publication date: 25-Nov-2020
https://doi.org/10.1109/IVCNZ51579.2020.9290617
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