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International Conference on Similarity Search and Applications

SISAP 2013: Similarity Search and Applications pp 91–102Cite as

Pivot Selection Strategies for Permutation-Based Similarity Search

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 8199)

Abstract

Recently, permutation based indexes have attracted interest in the area of similarity search. The basic idea of permutation based indexes is that data objects are represented as appropriately generated permutations of a set of pivots (or reference objects). Similarity queries are executed by searching for data objects whose permutation representation is similar to that of the query. This, of course assumes that similar objects are represented by similar permutations of the pivots.

In the context of permutation-based indexing, most authors propose to select pivots randomly from the data set, given that traditional pivot selection strategies do not reveal better performance. However, to the best of our knowledge, no rigorous comparison has been performed yet. In this paper we compare five pivots selection strategies on three permutation-based similarity access methods. Among those, we propose a novel strategy specifically designed for permutations. Two significant observations emerge from our tests. First, random selection is always outperformed by at least one of the tested strategies. Second, there is not a strategy that is universally the best for all permutation-based access methods; rather different strategies are optimal for different methods.

Keywords

  • permutation-based
  • pivot
  • metric space
  • similarity search
  • inverted files
  • content based image retrieval

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  • DOI: 10.1007/978-3-642-41062-8_10
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Authors and Affiliations

  1. Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo”, via G. Moruzzi, 1, Pisa, 56124, Italy

    Giuseppe Amato, Andrea Esuli & Fabrizio Falchi

Authors
  1. Giuseppe Amato
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  2. Andrea Esuli
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  3. Fabrizio Falchi
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Editor information

Editors and Affiliations

  1. Database Laboratory, Universidade da Coruña, Spain

    Nieves Brisaboa & Oscar Pedreira & 

  2. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Pavel Zezula

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Amato, G., Esuli, A., Falchi, F. (2013). Pivot Selection Strategies for Permutation-Based Similarity Search. In: Brisaboa, N., Pedreira, O., Zezula, P. (eds) Similarity Search and Applications. SISAP 2013. Lecture Notes in Computer Science, vol 8199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41062-8_10

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  • DOI: https://doi.org/10.1007/978-3-642-41062-8_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41061-1

  • Online ISBN: 978-3-642-41062-8

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