Experimental Analysis of Insertion Costs in a Naïve Dynamic MDF-Tree

  • Authors:
  • Luisa Micó;Jose Oncina

  • Affiliations:
  • Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Alicante, Spain E-03080;Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Alicante, Spain E-03080

  • Venue:
  • IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Similarity search is a widely employed technique in Pattern Recognition. In order to speed up the search many indexing techniques have been proposed. However, the majority of the proposed techniques are static, that is, a fixed training set is used to build up the index. This characteristic becomes a major problem when these techniques are used in dynamic (interactive) systems. In these systems updating the training set is necessary to improve its performance. In this work, we explore the surprising efficiency of a naïve algorithm that allows making incremental insertion in a previously known index: the MDF-tree.