MESSIF: Metric Similarity Search Implementation Framework

  • Michal Batko
  • David Novak
  • Pavel Zezula
Conference paper

DOI: 10.1007/978-3-540-77088-6_1

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4877)
Cite this paper as:
Batko M., Novak D., Zezula P. (2007) MESSIF: Metric Similarity Search Implementation Framework. In: Thanos C., Borri F., Candela L. (eds) Digital Libraries: Research and Development. Lecture Notes in Computer Science, vol 4877. Springer, Berlin, Heidelberg

Abstract

The similarity search has become a fundamental computational task in many applications. One of the mathematical models of the similarity – the metric space – has drawn attention of many researchers resulting in several sophisticated metric-indexing techniques. An important part of a research in this area is typically a prototype implementation and subsequent experimental evaluation of the proposed data structure. This paper describes an implementation framework called MESSIF that eases the task of building such prototypes. It provides a number of modules from basic storage management, over a wide support for distributed processing, to automatic collecting of performance statistics. Due to its open and modular design it is also easy to implement additional modules, if necessary. The MESSIF also offers several ready-to-use generic clients that allow to control and test the index structures.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Michal Batko
    • 1
  • David Novak
    • 1
  • Pavel Zezula
    • 1
  1. 1.Masaryk University, BrnoCzech Republic

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