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This study introduces an efficient approximate string matching method using generalized edit distance. By skipping unnecessary calculations over k-mismatches, it significantly reduces computation time, especially for small k values.

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Area of Science:

  • Computer Science
  • Bioinformatics
  • Computational Linguistics

Background:

  • Approximate string matching is crucial for tasks like sequence alignment and text searching.
  • Generalized edit distance offers sophisticated string comparison but incurs high computational costs.
  • Existing methods struggle with the computational complexity of generalized edit distance calculations.

Purpose of the Study:

  • To develop an optimized algorithm for approximate string matching with k-mismatches using generalized edit distance.
  • To reduce the execution time associated with complex edit distance computations.
  • To enhance the efficiency of string matching algorithms in resource-intensive applications.

Main Methods:

  • Proposing an approximate string matching algorithm that calculates generalized edit distance.
  • Implementing a pruning strategy to identify and skip computational steps exceeding k-mismatches.
  • Utilizing diagonal step calculations with a pruning register to avoid unnecessary distance computations.
  • Amortizing the overhead of control statements and memory access through multi-step skipping.

Main Results:

  • The proposed method significantly reduces execution time for approximate string matching.
  • The efficiency gains are particularly notable when the number of allowed mismatches (k) is small.
  • Practical implementations demonstrate substantial performance improvements over traditional methods.
  • The overhead introduced by the skipping mechanism is effectively managed.

Conclusions:

  • The developed approximate string matching algorithm offers a significant speedup for generalized edit distance calculations.
  • The k-mismatch skipping technique provides a practical solution for reducing computational costs in sophisticated string matching.
  • This approach is highly beneficial for applications requiring fast and accurate string comparisons with a limited tolerance for errors.