short-paper

A Genetic Programming Approach for Searching on Nearest Neighbors Graphs

Authors:

Javier A. Vargas Muñoz,

Ricardo da S. TorresAuthors Info & Claims

ICMR '19: Proceedings of the 2019 on International Conference on Multimedia Retrieval

Pages 43 - 47

https://doi.org/10.1145/3323873.3325014

Published: 05 June 2019 Publication History

Abstract

The use of nearest neighbors graphs has been leading to considerable gains over classic approaches (e.g., tree-indexing-based methods) in approximate nearest neighbor searches. Classical searches on these graphs are conduced in a greedy way by moving at each step to the neighbor (of current vertex) with the lowest distance to the query. In this work, we explore the combination of topological properties of graphs and the distance itself through a Genetic Programming framework to obtain a better indicator for selecting the next vertex in the search process. Our objective is to minimize the scan rate needed to reach the true nearest neighbors. Experimental results, conducted with three different graph-based methods over a large textual collection, show significant gains of the proposed approach over the classic search algorithm on graphs.

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Cited By

Muñoz JDias ZTorres R(2022)A genetic programming approach for searching on nearest neighbors graphsMultimedia Tools and Applications10.1007/s11042-022-12248-w81:16(23449-23472)Online publication date: 18-Mar-2022
https://doi.org/10.1007/s11042-022-12248-w
Wang MXu XYue QWang Y(2021)A comprehensive survey and experimental comparison of graph-based approximate nearest neighbor searchProceedings of the VLDB Endowment10.14778/3476249.347625514:11(1964-1978)Online publication date: 27-Oct-2021
https://dl.acm.org/doi/10.14778/3476249.3476255
Xu XWang MWang YMa D(2021)Two-stage routing with optimized guided search and greedy algorithm on proximity graph▪Knowledge-Based Systems10.1016/j.knosys.2021.107305229:COnline publication date: 11-Oct-2021
https://dl.acm.org/doi/10.1016/j.knosys.2021.107305

Index Terms

A Genetic Programming Approach for Searching on Nearest Neighbors Graphs
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Bio-inspired approaches
        Genetic programming
2. Information systems
  1. Information retrieval
  2. Information systems applications
    1. Data mining
      1. Nearest-neighbor search

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Published In

cover image ACM Conferences

ICMR '19: Proceedings of the 2019 on International Conference on Multimedia Retrieval

June 2019

427 pages

ISBN:9781450367653

DOI:10.1145/3323873

General Chairs:
Abdulmotaleb El Saddik
University of Ottawa, Canada
,
Alberto Del Bimbo
University of Florence, Italy
,
Zhongfei Zhang
Binghamton University, State University of New York, USA
,
Program Chairs:
Alexander Hauptmann
Carnegie Mellon University, USA
,
K. Selcuk Candan
Arizona State University, USA
,
Marco Bertini
University of Florence, Italy
,
Lexing Xie
Australia National University, Australia
,
Xiao-Yong Wei
Sichuan University, China

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 June 2019

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Fundação de Amparo à Pesquisa do Estado de São Paulo
Conselho Nacional de Desenvolvimento Científico e Tecnológico

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ICMR '19

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SIGMM

ICMR '19: International Conference on Multimedia Retrieval

June 10 - 13, 2019

Ottawa ON, Canada

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Overall Acceptance Rate 177 of 599 submissions, 30%

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Cited By

Muñoz JDias ZTorres R(2022)A genetic programming approach for searching on nearest neighbors graphsMultimedia Tools and Applications10.1007/s11042-022-12248-w81:16(23449-23472)Online publication date: 18-Mar-2022
https://doi.org/10.1007/s11042-022-12248-w
Wang MXu XYue QWang Y(2021)A comprehensive survey and experimental comparison of graph-based approximate nearest neighbor searchProceedings of the VLDB Endowment10.14778/3476249.347625514:11(1964-1978)Online publication date: 27-Oct-2021
https://dl.acm.org/doi/10.14778/3476249.3476255
Xu XWang MWang YMa D(2021)Two-stage routing with optimized guided search and greedy algorithm on proximity graph▪Knowledge-Based Systems10.1016/j.knosys.2021.107305229:COnline publication date: 11-Oct-2021
https://dl.acm.org/doi/10.1016/j.knosys.2021.107305

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