The Normalized Edit Distance with Uniform Operation Costs Is a Metric

Authors Dana Fisman, Joshua Grogin, Oded Margalit, Gera Weiss



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Author Details

Dana Fisman
  • Dept. of Computer Science, Ben-Gurion University, Beer-Sheva, Israel
Joshua Grogin
  • Dept. of Computer Science, Ben-Gurion University, Beer-Sheva, Israel
Oded Margalit
  • Dept. of Computer Science, Ben-Gurion University, Beer-Sheva, Israel
Gera Weiss
  • Dept. of Computer Science, Ben-Gurion University, Beer-Sheva, Israel

Cite As Get BibTex

Dana Fisman, Joshua Grogin, Oded Margalit, and Gera Weiss. The Normalized Edit Distance with Uniform Operation Costs Is a Metric. In 33rd Annual Symposium on Combinatorial Pattern Matching (CPM 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 223, pp. 17:1-17:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022) https://doi.org/10.4230/LIPIcs.CPM.2022.17

Abstract

We prove that the normalized edit distance proposed in [Marzal and Vidal 1993] is a metric when the cost of all the edit operations are the same. This closes a long standing gap in the literature where several authors noted that this distance does not satisfy the triangle inequality in the general case, and that it was not known whether it is satisfied in the uniform case - where all the edit costs are equal. We compare this metric to two normalized metrics proposed as alternatives in the literature, when people thought that Marzal’s and Vidal’s distance is not a metric, and identify key properties that explain why the original distance, now known to also be a metric, is better for some applications. Our examination is from a point of view of formal verification, but the properties and their significance are stated in an application agnostic way.

Subject Classification

ACM Subject Classification
  • Theory of computation → Pattern matching
Keywords
  • edit distance
  • normalized distance
  • triangle inequality
  • metric

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References

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