Graphs and Networks
About this book
Graphs and Networks
A unique blend of graph theory and network science for mathematicians and data science professionals alike.
Featuring topics such as minors, connectomes, trees, distance, spectral graph theory, similarity, centrality, small-world networks, scale-free networks, graph algorithms, Eulerian circuits, Hamiltonian cycles, coloring, higher connectivity, planar graphs, flows, matchings, and coverings, Graphs and Networks contains modern applications for graph theorists and a host of useful theorems for network scientists.
The book begins with applications to biology and the social and political sciences and gradually takes a more theoretical direction toward graph structure theory and combinatorial optimization. A background in linear algebra, probability, and statistics provides the proper frame of reference.
Graphs and Networks also features:
- Applications to neuroscience, climate science, and the social and political sciences
- A research outlook integrated directly into the narrative with ideas for students interested in pursuing research projects at all levels
- A large selection of primary and secondary sources for further reading
- Historical notes that hint at the passion and excitement behind the discoveries
- Practice problems that reinforce the concepts and encourage further investigation and independent work
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Information
Table of contents
- Cover
- Table of Contents
- Title Page
- Copyright
- Dedication
- List of Figures
- Preface
- 1 From Königsberg to Connectomes
- 2 Fundamental Topics
- 3 Similarity and Centrality
- 4 Types of Networks
- 5 Graph Algorithms
- 6 Structure, Coloring, Higher Connectivity
- 7 Planar Graphs
- 8 Flows and Matchings
- Appendix A: Linear Algebra
- Appendix B: Probability and Statistics
- Appendix C: Appendix CComplexity of Algorithms
- Appendix D: Appendix DStacks and Queues
- Bibliography
- Index
- End User License Agreement