Program Systems: Theory and Applications, 2017, Volume 8, Issue 4, Pages 347–357
This article is cited in 2 scientific papers (total in 2 papers)
Mathematical Foundations of Programming
Model and axioms for similarity metrics
S. V. Znamenskij
Ailamazyan Program Systems Institute of Russian Academy of Sciences
Modern applications usually combine different similarity metrics taking into account the algorithms complexity, the peculiarities of human perception, data resources and samples.
The optimization requires a unified formal description of the basic similarity metrics.
The system of the similarity metric axioms is enchanced and its universal model is constructed which generalizes known models of similarity that do not reduce to the Euclidean metric.
The model is based on a weighted partially ordered set. (In Russian).
Key words and phrases:
similarity of strings, sequence alignment, edit distance, LCS, Levenshtein metric.
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MSC: 97P20; 91C05, 91C20
S. V. Znamenskij, “Model and axioms for similarity metrics”, Program Systems: Theory and Applications, 8:4 (2017), 347–357
Citation in format AMSBIB
\paper Model and axioms for similarity metrics
\jour Program Systems: Theory and Applications
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This publication is cited in the following articles:
S. V. Znamenskij, “Stable assessment of the quality of similarity algorithms
of character strings and their normalizations”, Programmnye sistemy: teoriya i prilozheniya, 9:4 (2018), 561–578
S. V. Znamenskii, “Ustoichivaya otsenka kachestva algoritmov skhodstva simvolnykh strok i ikh normalizatsii”, Programmnye sistemy: teoriya i prilozheniya, 9:4 (2018), 579–596
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