A filter method for the weighted local similarity search problem

  • Enno Ohlebusch
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1264)


In contrast to the extensively studied k-differences problem, in the weighted local similarity search problem one searches for approximate matches of subwords of a pattern and subwords of a text whose lengths exceed a certain threshold. Moreover, arbitrary gap and substitution weights are allowed. In this paper, two new prefilter algorithms for the weighted local similarity search problem are presented. These overcome the disadvantages of a similar filter algorithm devised by Myers.


Cost Function Dynamic Programming Edit Distance Filtration Efficiency Edit Operation 
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 1997

Authors and Affiliations

  • Enno Ohlebusch
    • 1
  1. 1.University of BielefeldTechnische FakultätBielefeldGermany

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