On Two-Dimensional Approximate Pattern Matching Using Fuzzy Automata

Title

On Two-Dimensional Approximate Pattern Matching Using Fuzzy Automata

Creator

John Kaspar A.; Sheena Christy D.K.

Description

Pattern matching has been extensively studied in the last few decades, owing to its great contribution in various fields such as search engines, computational biology, etc. Several real-life situations require patterns that allow ambiguity in specified positions. In this paper, one-dimensional and two-dimensional approximate pattern matching models have been constructed using fuzzy automata. The similarity function used in fuzzy automata enables the occurrence of all exact and similar one-dimensional and two-dimensional patterns. This kind of searching approximate patterns is not possible with regular search models. The time complexity of the proposed algorithm has also been analyzed. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Source

Lecture Notes in Networks and Systems, Vol-994 LNNS, pp. 595-612.

Date

2024-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Array matching; Fuzzy automata; Pattern matching; Position specific approximate pattern matching

Coverage

John Kaspar A., Department of mathematics, Christ University, Karnataka, Bengaluru, 560029, India; Sheena Christy D.K., Department of mathematics, SRM Institute of Science and Technology, Tamil Nadu, Kattankulathur, 603203, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981973179-4

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-97-3180-0_39

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200685063&doi=10.1007%2f978-981-97-3180-0_39&partnerID=40&md5=9c169fd8faaf1ebc54f057a5d4afa4e5