Könyv Quantitative Graph Theory Matthias Dehmer

Quantitative Graph Theory

Szerző: Matthias Dehmer
Nyelv: Angol
Kötés: Kemény kötésű
Elérhetőség: 50 % esély
Keressük az egész világon
107 554 Ft
The first book devoted exclusively to quantitative graph theory, Quantitative Graph Theory: Mathemat...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2014
oldal
528
EAN
9781466584518
ISBN
9781466584518
Enbook ID
09060944
Súly
930
Méretek
237 x 163 x 35

Teljes leírás

The first book devoted exclusively to quantitative graph theory, Quantitative Graph Theory: Mathematical Foundations and Applications presents and demonstrates existing and novel methods for analyzing graphs quantitatively. Incorporating interdisciplinary knowledge from graph theory, information theory, measurement theory, and statistical techniques, this book covers a wide range of quantitative-graph theoretical concepts and methods, including those pertaining to real and random graphs such as:





  • Comparative approaches (graph similarity or distance)


  • Graph measures to characterize graphs quantitatively


  • Applications of graph measures in social network analysis and other disciplines


  • Metrical properties of graphs and measures


  • Mathematical properties of quantitative methods or measures in graph theory


  • Network complexity measures and other topological indices


  • Quantitative approaches to graphs using machine learning (e.g., clustering)


  • Graph measures and statistics


  • Information-theoretic methods to analyze graphs quantitatively (e.g., entropy)




Through its broad coverage, Quantitative Graph Theory: Mathematical Foundations and Applications fills a gap in the contemporary literature of discrete and applied mathematics, computer science, systems biology, and related disciplines. It is intended for researchers as well as graduate and advanced undergraduate students in the fields of mathematics, computer science, mathematical chemistry, cheminformatics, physics, bioinformatics, and systems biology.

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