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Algorithms for Matching Strings with Fuzzy Context-Free and Automata Patterns

  • PART III “PATTERN RECOGNITION AND APPLICATIONS”
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Abstract

This paper is devoted to determining the degree of compliance of a given string with a pattern represented as a grammar, the terminal symbols of which are fuzzy properties of the characters of the base alphabet. In the case when the pattern is specified as a context-free grammar in the Chomsky normal form, the matching degree is calculated by applying a fuzzy version of the Cocke–Younger–Kasami (CYK) algorithm in cubic time depending on the length of the input string. The proposed algorithm becomes a linear time algorithm for the subclass of the automata grammars, which can be considered as finite automata with fuzzy properties of alphabetic characters on transitions. This work may find application in bioinformatics to classify deoxyribonucleic acid (DNA) sequences using fuzzy prototypes described in one way or another. Other applications are related to fuzzy analysis of natural languages, pattern recognition and determination of fuzzy regularity of a string.

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Funding

This work was supported by the Ministry of Education, Science, Culture and Sports of the Republic of Armenia, project 21T-1B326.

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Authors and Affiliations

  1. IT Educational and Research Center of Yerevan State University, 0025, Yerevan, Armenia

    A. H. Kostanyan

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  1. A. H. Kostanyan
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Correspondence to A. H. Kostanyan.

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The author of this work declares that he has no conflicts of interest.

Additional information

Armen Kostanyan is an Associate Professor at Yerevan State University and an Adjunct Associate Professor at American University of Armenia. He obtained the academic degree of Associate Professor in 2006, and the PhD in 1997. He is the author or co-author of 30 scientific publications.

Research interests: computational system analysis and design, fuzzy string processing, predictive calculations under uncertainty.

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Kostanyan, A.H. Algorithms for Matching Strings with Fuzzy Context-Free and Automata Patterns. Pattern Recognit. Image Anal. 34, 110–115 (2024). https://doi.org/10.1134/S1054661824010115

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  • DOI: https://doi.org/10.1134/S1054661824010115

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