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Permutation-Based Pruning for Approximate K-NN Search

  • Hisham Mohamed
  • Stéphane Marchand-Maillet
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8055)

Abstract

In this paper, we propose an effective indexing and search algorithms for approximate K-NN based on an enhanced implementation of the Metric Suffix Array and Permutation-Based Indexing. Our main contribution is to propose a sound scalable strategy to prune objects based on the location of the reference objects in the query ordered lists. We study the performance and efficiency of our algorithms on large-scale dataset of millions of documents. Experimental results show a decrease of computational time while preserving the quality of the results.

Keywords

Metric Suffix Array (MSA) Permutation-Based Indexing Approximate Similarity Search Large-Scale Multimedia Indexing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hisham Mohamed
    • 1
  • Stéphane Marchand-Maillet
    • 1
  1. 1.Université de GenèveGenevaSwitzerland

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