Quantifying topological indices in bipartite and tripartite graphs using Lyndon words and Python algorithms

Lyndon Word Representable Graphs (LWRGs) present a novel intersection between graph structures and symbolic sequences, with significant implications for chemical graph theory. This study enhances the understanding of LWRGs by deriving specific topological indices for binary and ternary core words. B...

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Veröffentlicht in:International journal of information technology (Singapore. Online) Jg. 17; H. 2; S. 1247 - 1258
Hauptverfasser: Sethukkarasi, A., Vidyanandini, S., Arulprakasam, R.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Singapore Springer Nature Singapore 01.03.2025
Springer Nature B.V
Schlagworte:
Artificial Intelligence
Computer Imaging
Computer Science
Graph theory
Graphical representations
Graphs
Image Processing and Computer Vision
Machine Learning
Network analysis
Original Research
Pattern Recognition and Graphics
Software Engineering
Topology
Vision
Lyndon words
Binary words
Lyndon word representable graphs
Topological indices
Bipartite graphs
ISSN:2511-2104, 2511-2112
Online-Zugang:Volltext
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Zusammenfassung:Lyndon Word Representable Graphs (LWRGs) present a novel intersection between graph structures and symbolic sequences, with significant implications for chemical graph theory. This study enhances the understanding of LWRGs by deriving specific topological indices for binary and ternary core words. By linking LWRGs to topological indices, we provide new insights into the structural relationships between words and graphs. This interdisciplinary approach highlights the utility of Lyndon words in representing graph properties and underscores the relevance of topological indices in various applications, from network analysis to molecular chemistry.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:2511-2104
2511-2112
DOI:10.1007/s41870-024-02303-0