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Line Graphs and Line Digraphs
In the present era dominated by computers, graph theory has come into its own as an area of mathematics, prominent for both its theory and its applications. One of the richest and most studied types of graph structures is that of the line graph, where the focus is more on the edges of a graph than on the vertices. A subject worthy of exploration in itself, line graphs are closely connected to other areas of mathematics and computer science. This book is unique in its extensive coverage of many areas of graph theory applicable to line graphs. The book has three parts. Part I covers line graphs and their properties, while Part II looks at features that apply specifically to directed graphs, and Part III presents generalizations and variations of both line graphs and line digraphs. Line Graphs and Line Digraphs is the first comprehensive monograph on the topic. With minimal prerequisites, the book is accessible to most mathematicians and computer scientists who have had an introduction graph theory, and will be a valuable reference for researchers working in graph theory and related fields.
Functions and Graphs
This text demonstrates the fundamentals of graph theory. The first part employs simple functions to analyze basics; second half deals with linear functions, quadratic trinomials, linear fractional functions, power functions, rational functions. 1969 edition.
Algorithmic Graph Theory and Perfect Graphs
Algorithmic Graph Theory and Perfect Graphs, first published in 1980, has become the classic introduction to the field. This new Annals edition continues to convey the message that intersection graph models are a necessary and important tool for solving real-world problems. It remains a stepping stone from which the reader may embark on one of many fascinating research trails. The past twenty years have been an amazingly fruitful period of research in algorithmic graph theory and structured families of graphs. Especially important have been the theory and applications of new intersection graph models such as generalizations of permutation graphs and interval graphs. These have lead to new families of perfect graphs and many algorithmic results. These are surveyed in the new Epilogue chapter in this second edition. - New edition of the "Classic" book on the topic - Wonderful introduction to a rich research area - Leading author in the field of algorithmic graph theory - Beautifully written for the new mathematician or computer scientist - Comprehensive treatment
Graphs and Charts Activity Book
Discover all kinds of graphs and charts and how to use them in this entertaining activity book. The activities encourage children to collect and analyse data, from tallying the number of animals spotted on safari, to displaying types of weather on a bar chart and sorting animals into a Venn diagram. Quizzes after each section let children test what they've learned.
Eigenspaces of Graphs
Current research on the spectral theory of finite graphs may be seen as part of a wider effort to forge closer links between algebra and combinatorics (in particular between linear algebra and graph theory).This book describes how this topic can be strengthened by exploiting properties of the eigenspaces of adjacency matrices associated with a graph. The extension of spectral techniques proceeds at three levels: using eigenvectors associated with an arbitrary labelling of graph vertices, using geometrical invariants of eigenspaces such as graph angles and main angles, and introducing certain kinds of canonical eigenvectors by means of star partitions and star bases. One objective is to describe graphs by algebraic means as far as possible, and the book discusses the Ulam reconstruction conjecture and the graph isomorphism problem in this context. Further problems of graph reconstruction and identification are used to illustrate the importance of graph angles and star partitions in relation to graph structure. Specialists in graph theory will welcome this treatment of important new research.
Graph Representation Learning
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical sy...
Symmetry in Graphs
The first full-length book on the theme of symmetry in graphs, a fast-growing topic in algebraic graph theory.
Knowledge Graphs
This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced ...
Introduction to Random Graphs
The text covers random graphs from the basic to the advanced, including numerous exercises and recommendations for further reading.
An Atlas of Graphs
Graph theory is a fast-developing discipline and has, over the past few decades, been seen to have important applications, particularly in operations research and in computer science. For this reason there is a need for a reference in the area, comprehensively cataloguing the properties of graphs and accessible to both graph theorists and other researchers. This book contains a wealth of information, including over 10000 diagrams and extensive tables of associated properties. It is the first book to present this information on such a scale, and as such will be an invaluable resource.
