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Record Nr. |
UNINA9910787301403321 |
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Titolo |
Quantitative graph theory : mathematical foundations and applications / / edited by Matthias Dehmer, Institute for Theoretical Computer Science, Mathematics and Operations Research, Department of Computer Science, Universitat der Bundeswehr Munc |
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Pubbl/distr/stampa |
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Boca Raton : , : CRC Press, , [2015] |
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©2015 |
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ISBN |
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0-429-10326-3 |
1-4665-8452-1 |
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Descrizione fisica |
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1 online resource (516 p.) |
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Collana |
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Discrete mathematics and its applications |
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Classificazione |
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COM046000MAT036000SCI008000 |
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Disciplina |
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Soggetti |
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Graph theory - Data processing |
Combinatorial analysis |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Front Cover; Dedication; Contents; Preface; Editors; Contributors; Chapter 1 What Is Quantitative Graph Theory?; Chapter 2 Localization of Graph Topological Indices via Majorization Technique; Chapter 3 Wiener Index of Hexagonal Chains with Segments of Equal Length; Chapter 4 Metric-Extremal Graphs; Chapter 5 Quantitative Methods for Nowhere-Zero Flows and Edge Colorings; Chapter 6 Width-Measures for Directed Graphs and Algorithmic Applications; Chapter 7 Betweenness Centrality in Graphs; Chapter 8 On a Variant Szeged and PI* Indices of Thorn Graphs; Chapter 9 Wiener Index of Line Graphs |
Chapter 10 Single-Graph Support MeasuresChapter 11 Network Sampling Algorithms and Applications; Chapter 12 Discrimination of Image Textures Using Graph Indices; Chapter 13 Network Analysis Applied to the Political Networks of Mexico; Chapter 14 Social Network Centrality, MovementIdentification, and the Participation ofIndividuals in a Social Movement: The Case of the Canadian Environmental Movement; Chapter 15 Graph Kernels in Chemoinformatics; Chapter 16 Chemical Compound Complexity in Biological Pathways; Back Cover |
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Sommario/riassunto |
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This book presents methods for analyzing graphs and networks |
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quantitatively. Incorporating interdisciplinary knowledge from graph theory, information theory, measurement theory, and statistical techniques, it covers a wide range of quantitative graph-theoretical concepts and methods, including those pertaining to random graphs. Through its broad coverage, the book fills a gap in the contemporary literature of discrete and applied mathematics, computer science, systems biology, and related disciplines-- |
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