Efficient Group of Permutants for Proximity Searching

  • Karina Figueroa Mora
  • Rodrigo Paredes
  • Roberto Rangel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6718)


Modeling proximity searching problems in a metric space allows one to approach many problems in different areas, e.g. pattern recognition, multimedia search, or clustering. Recently there was proposed the permutation based approach, a novel technique that is unbeatable in practice but difficult to compress. In this article we introduce an improvement on that metric space search data structure. Our technique shows that we can compress the permutation based algorithm without loosing precision. We show experimentally that our technique is competitive with the original idea and improves it up to 46% in real databases.


Original Idea Modeling Proximity Real Database Synthetic Database Machine Word 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Karina Figueroa Mora
    • 1
  • Rodrigo Paredes
    • 2
  • Roberto Rangel
    • 1
  1. 1.Universidad Michoacana de San Nicolás de HidalgoMéxico
  2. 2.Universidad de TalcaChile

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