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Similarity Join in Metric Spaces Using eD-Index

  • Vlastislav Dohnal
  • Claudio Gennaro
  • Pavel Zezula
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2736)

Abstract

Similarity join in distance spaces constrained by the metric postulates is the necessary complement of more famous similarity range and the nearest neighbor search primitives. However, the quadratic computational complexity of similarity joins prevents from applications on large data collections. We present the eD-Index, an extension of D-index, and we study an application of the eD-Index to implement two algorithms for similarity self joins, i.e. the range query join and the overloading join. Though also these approaches are not able to eliminate the intrinsic quadratic complexity of similarity joins, significant performance improvements are confirmed by experiments.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Vlastislav Dohnal
    • 1
  • Claudio Gennaro
    • 2
  • Pavel Zezula
    • 1
  1. 1.Masaryk UniversityBrnoCzech Republic
  2. 2.ISTI-CNRPisaItaly

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