Partial Symbol Ordering Distance

  • Javier Herranz
  • Jordi Nin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5861)


Nowadays sequences of symbols are becoming more important, as they are the standard format for representing information in a large variety of domains such as ontologies, sequential patterns or non numerical attributes in databases. Therefore, the development of new distances for this kind of data is a crucial need. Recently, many similarity functions have been proposed for managing sequences of symbols; however, such functions do not always hold the triangular inequality. This property is a mandatory requirement in many data mining algorithms like clustering or k-nearest neighbors algorithms, where the presence of a metric space is a must. In this paper, we propose a new distance for sequences of (non-repeated) symbols based on the partial distances between the positions of the common symbols. We prove that this Partial Symbol Ordering distance satisfies the triangular inequality property, and we finally describe a set of experiments supporting that the new distance outperforms the Edit distance in those scenarios where sequence similarity is related to the positions occupied by the symbols.


Sequences of Symbols Distances Triangular Inequality 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Javier Herranz
    • 1
  • Jordi Nin
    • 2
  1. 1.Dept. Matemàtica Aplicada IVUniversitat Politècnica de CatalunyaBarcelona(Spain)
  2. 2.LAAS, Laboratoire d’Analyse et d’Architecture des SystèmesCNRS, Centre National de la Recherche ScientifiqueToulouse(France)

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