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• Graph Algorithms: Practical Examples in Apache Spark and Neo4j

This book is a practical guide to getting started with graph algorithms for developers and data scientists who have experience using Apache Spark or Neo4j. You'll walk through hands-on examples that show you how to use graph algorithms in Apache Spark/Neo4j.

• Graph Theory - Advanced Algorithms and Applications

Not only will the methods and explanations help you to understand more about graph theory, but you will find it joyful to discover ways that you can apply graph theory in your applications or scientific research.

• Probability on Trees and Networks (Russell Lyons, et al)

This book is concerned with certain aspects of discrete probability on infinite graphs that are currently in vigorous development. Of course, finite graphs are analyzed as well, but usually with the aim of understanding infinite graphs and networks.

• Graph Theory and Complex Networks (Maarten van Steen)

This book aims to explain the basics of graph theory that are needed at an introductory level for students in computer or information sciences. It also aims to provide an introduction to the modern field of network science.

• Graph Theory (Reinhard Diestel)

This book covers the core material of the subject with concise yet reliably complete proofs, while offering glimpses of more advanced methods in each field by one or two deeper results, again with proofs given in full detail.

• An Introduction to Combinatorics and Graph Theory

This book walks the reader through the classic parts of Combinatorics and graph theory, while also discussing some recent progress in the area: on the one hand, providing material that will help students learn the basic techniques.

• Graph Databases: New Opportunities for Connected Data

This book provides a practical foundation for those who want to apply Graph Database to real-world business solutions. You'll learn why graph database are useful, where they're applicable, and how to design and implement solutions that use them.

• Algorithmic Graph Theory (David Joyner, et al)

This is an introductory book on algorithmic graph theory. Theory and algorithms are illustrated using the Sage open source mathematics software. It's especially suitable for computer scientists and mathematicians interested in computational complexity.

• Advances in Graph Algorithms (Ton Kloks, Yue-Li Wang)

This is a book about some currently popular topics such as exponential algorithms, fixed-parameter algorithms and algorithms using decomposition trees of graphs which is one of focuses of the book - occupied a whole chapter.

• Graph Theory with Applications (J.A. Bondy and U.S.R. Murty)

The primary aim of this book is to present a coherent introduction to graph theory, suitable as a textbook for advanced undergraduate and beginning graduate students in mathematics and computer science.

• Graph Theory Lessons (Christopher P. Mawata)

This text covers the important elementary topics of graph theory and its applications. In addition, he presents a large variety of proofs designed to strengthen mathematical techniques and offers challenging opportunities to have fun with mathematics.

• Introduction to Graph Theory: Definitions, Traversal, Analysis, etc.

Requiring only high school algebra as mathematical background, the book leads the reader from simple graphs through planar graphs, Euler's formula, Platonic graphs, coloring, the genus of a graph, Euler walks, Hamilton walks, and a discussion of The Seven Bridges of Konigsberg.

• New Frontiers in Graph Theory (Yagang Zhang)

The purpose of this book is not only to present the latest state and development tendencies of graph theory, but to bring the reader far enough along the way to enable him to embark on the research problems of his own.

• Fractional Graph Theory: A Rational Approach (E. Scheinerman)

In this book the authors explore generalizations of core graph theory notions by allowing real values to substitute where normally only integers would be permitted. The aim is to prove "fractional analogues" of the theorems of traditional graph theory.

• Digraphs: Theory, Algorithms and Applications (J. Bang-Jensen)

This book is an essential, comprehensive reference of Digraphs for students, and researchers in mathematics, operations research and computer science.

• Algorithms and Data Structures: Apps to Graphics and Geometry

An introductory coverage of algorithms and data structures with application to graphics and geometry. Sample exercises, many with solutions, are included throughout the book.

• Lists, Decisions and Graphs - With an Introduction to Probability

In this book, four basic areas of discrete mathematics are presented: Counting and Listing (Unit CL), Functions (Unit Fn), Decision Trees and Recursion (Unit DT), and Basic Concepts in Graph Theory (Unit GT).

• Introductory Map Theory (Yanpei Liu)

As an introductory book, this book contains the elementary materials in map theory, including embeddings of a graph, abstract maps, duality, orientable and non-orientable maps, isomorphisms of maps and the enumeration of rooted or unrooted maps, etc.

• Graph and Network Theory in Physics: A Short Introduction

This book consists of some of the main areas of research in graph and network theory applied to physics.

• Functional Programming and Parallel Graph Rewriting

This is an introduction to the techniques of functional programming, focusing on an alternative computational model - Graph Rewriting Systems.

• Architecture for Combinator Graph Reduction (Philip J. Koopman)

The results of cache-simulation experiments with an abstract machine for reducing combinator graphs are presented.

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