Graph Based Modelling In Science Technology And Art

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Graph-Based Modelling in Science, Technology and Art

Author : Stanisław Zawiślak
Publisher : Springer Nature
ISBN 13 : 3030767876
Total Pages : 311 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Graph-Based Modelling in Science, Technology and Art by : Stanisław Zawiślak

Download or read book Graph-Based Modelling in Science, Technology and Art written by Stanisław Zawiślak and published by Springer Nature. This book was released on 2021-08-01 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents interdisciplinary, cutting-edge and creative applications of graph theory and modeling in science, technology, architecture and art. Topics are divided into three parts: the first one examines mechanical problems related to gears, planetary gears and engineering installations; the second one explores graph-based methods applied to medical analyses as well as biological and chemical modeling; and the third part includes various topics e.g. drama analysis, aiding of design activities and network visualisation. The authors represent several countries in Europe and America, and their contributions show how different, useful and fruitful the utilization of graphs in modelling of engineering systems can be. The book has been designed to serve readers interested in the subject of graph modelling and those with expertise in related areas, as well as members of the worldwide community of graph modelers.

Graph-Based Modelling in Engineering

Author : Stanisław Zawiślak
Publisher : Springer
ISBN 13 : 3319390201
Total Pages : 239 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Graph-Based Modelling in Engineering by : Stanisław Zawiślak

Download or read book Graph-Based Modelling in Engineering written by Stanisław Zawiślak and published by Springer. This book was released on 2016-09-30 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents versatile, modern and creative applications of graph theory in mechanical engineering, robotics and computer networks. Topics related to mechanical engineering include e.g. machine and mechanism science, mechatronics, robotics, gearing and transmissions, design theory and production processes. The graphs treated are simple graphs, weighted and mixed graphs, bond graphs, Petri nets, logical trees etc. The authors represent several countries in Europe and America, and their contributions show how different, elegant, useful and fruitful the utilization of graphs in modelling of engineering systems can be.

Graph-Powered Machine Learning

Author : Alessandro Negro
Publisher : Simon and Schuster
ISBN 13 : 163835393X
Total Pages : 494 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Graph-Powered Machine Learning by : Alessandro Negro

Download or read book Graph-Powered Machine Learning written by Alessandro Negro and published by Simon and Schuster. This book was released on 2021-10-05 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: Upgrade your machine learning models with graph-based algorithms, the perfect structure for complex and interlinked data. Summary In Graph-Powered Machine Learning, you will learn: The lifecycle of a machine learning project Graphs in big data platforms Data source modeling using graphs Graph-based natural language processing, recommendations, and fraud detection techniques Graph algorithms Working with Neo4J Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You’ll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you optimize with best design practices. Author Alessandro Negro’s extensive experience shines through in every chapter, as you learn from examples and concrete scenarios based on his work with real clients! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Identifying relationships is the foundation of machine learning. By recognizing and analyzing the connections in your data, graph-centric algorithms like K-nearest neighbor or PageRank radically improve the effectiveness of ML applications. Graph-based machine learning techniques offer a powerful new perspective for machine learning in social networking, fraud detection, natural language processing, and recommendation systems. About the book Graph-Powered Machine Learning teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and tools. In this authoritative book, you’ll master the architectures and design practices of graphs, and avoid common pitfalls. Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks. What's inside Graphs in big data platforms Recommendations, natural language processing, fraud detection Graph algorithms Working with the Neo4J graph database About the reader For readers comfortable with machine learning basics. About the author Alessandro Negro is Chief Scientist at GraphAware. He has been a speaker at many conferences, and holds a PhD in Computer Science. Table of Contents PART 1 INTRODUCTION 1 Machine learning and graphs: An introduction 2 Graph data engineering 3 Graphs in machine learning applications PART 2 RECOMMENDATIONS 4 Content-based recommendations 5 Collaborative filtering 6 Session-based recommendations 7 Context-aware and hybrid recommendations PART 3 FIGHTING FRAUD 8 Basic approaches to graph-powered fraud detection 9 Proximity-based algorithms 10 Social network analysis against fraud PART 4 TAMING TEXT WITH GRAPHS 11 Graph-based natural language processing 12 Knowledge graphs

Bond Graph Modelling for Control, Fault Diagnosis and Failure Prognosis

Author : Wolfgang Borutzky
Publisher : Springer Nature
ISBN 13 : 3030609677
Total Pages : 325 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Bond Graph Modelling for Control, Fault Diagnosis and Failure Prognosis by : Wolfgang Borutzky

Download or read book Bond Graph Modelling for Control, Fault Diagnosis and Failure Prognosis written by Wolfgang Borutzky and published by Springer Nature. This book was released on 2020-12-17 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows in a comprehensive presentation how Bond Graph methodology can support model-based control, model-based fault diagnosis, fault accommodation, and failure prognosis by reviewing the state-of-the-art, presenting a hybrid integrated approach to Bond Graph model-based fault diagnosis and failure prognosis, and by providing a review of software that can be used for these tasks. The structured text illustrates on numerous small examples how the computational structure superimposed on an acausal bond graph can be exploited to check for control properties such as structural observability and control lability, perform parameter estimation and fault detection and isolation, provide discrete values of an unknown degradation trend at sample points, and develop an inverse model for fault accommodation. The comprehensive presentation also covers failure prognosis based on continuous state estimation by means of filters or time series forecasting. This book has been written for students specializing in the overlap of engineering and computer science as well as for researchers, and for engineers in industry working with modelling, simulation, control, fault diagnosis, and failure prognosis in various application fields and who might be interested to see how bond graph modelling can support their work. Presents a hybrid model-based, data-driven approach to failure prognosis Highlights synergies and relations between fault diagnosis and failure prognostic Discusses the importance of fault diagnosis and failure prognostic in various fields

Graph-based Natural Language Processing and Information Retrieval

Author : Rada Mihalcea
Publisher : Cambridge University Press
ISBN 13 : 1139498827
Total Pages : 201 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Graph-based Natural Language Processing and Information Retrieval by : Rada Mihalcea

Download or read book Graph-based Natural Language Processing and Information Retrieval written by Rada Mihalcea and published by Cambridge University Press. This book was released on 2011-04-11 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications and different potential end-users. However, recent research has shown that these disciplines are intimately connected, with a large variety of natural language processing and information retrieval applications finding efficient solutions within graph-theoretical frameworks. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. It brings together topics as diverse as lexical semantics, text summarization, text mining, ontology construction, text classification and information retrieval, which are connected by the common underlying theme of the use of graph-theoretical methods for text and information processing tasks. Readers will come away with a firm understanding of the major methods and applications in natural language processing and information retrieval that rely on graph-based representations and algorithms.

Learning Neo4j

Author : Rik Van Bruggen
Publisher : Packt Publishing Ltd
ISBN 13 : 1849517177
Total Pages : 296 pages
Book Rating : 4.8/5 (495 download)

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Book Synopsis Learning Neo4j by : Rik Van Bruggen

Download or read book Learning Neo4j written by Rik Van Bruggen and published by Packt Publishing Ltd. This book was released on 2014-08-25 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for developers who want an alternative way to store and process data within their applications. No previous graph database experience is required; however, some basic database knowledge will help you understand the concepts more easily.

Bond Graph Methodology

Author : Wolfgang Borutzky
Publisher : Springer Science & Business Media
ISBN 13 : 1848828829
Total Pages : 673 pages
Book Rating : 4.8/5 (488 download)

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Book Synopsis Bond Graph Methodology by : Wolfgang Borutzky

Download or read book Bond Graph Methodology written by Wolfgang Borutzky and published by Springer Science & Business Media. This book was released on 2009-11-26 with total page 673 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, engineering systems are of ever-increasing complexity and must be c- sidered asmultidisciplinary systems composed of interacting subsystems or system components from different engineering disciplines. Thus, an integration of various engineering disciplines, e.g, mechanical, electrical and control engineering in ac- current design approach is required. With regard to the systematic development and analysis of system models,interdisciplinary computer aided methodologies are - coming more and more important. A graphical description formalism particularly suited for multidisciplinary s- tems arebondgraphs devised by Professor Henry Paynter in as early as 1959 at the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts, USA and in use since then all over the world. This monograph is devoted exclusively to the bond graph methodology. It gives a comprehensive, in-depth, state-of-the-art presentation including recent results sc- tered over research articles and dissertations and research contributions by the - thor to a number of topics. The book systematically covers the fundamentals of developing bond graphs and deriving mathematical models from them, the recent developments in meth- ology, symbolic and numerical processing of mathematical models derived from bond graphs. Additionally it discusses modern modelling languages, the paradigm of object-oriented modelling, modern software that can be used for building and for processing of bond graph models, and provides a chapter with small case studies illustrating various applications of the methodology.

Graph Theory

Author : Alessandra Cavalcante
Publisher : Nova Science Publishers
ISBN 13 : 9781628085433
Total Pages : 0 pages
Book Rating : 4.0/5 (854 download)

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Book Synopsis Graph Theory by : Alessandra Cavalcante

Download or read book Graph Theory written by Alessandra Cavalcante and published by Nova Science Publishers. This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graphs can be used to model many types of relations and process dynamics in physical, biological, social and information systems. Many practical problems can be represented by graphs. In this book, the authors present new research on graph theory including the applications of graph theory in architectural analysis; Miesian intersections and comparing and evaluating graph theory approaches to architectural spatial analysis; the algebraic structure of graphs; the combination of graph theory and unsupervised learning applied to social data mining; organising and structuring the contents of mathematical subjects using graph theory; and a modularity-based filtering approach for network immunisation.

Drawing Graphs

Author : Michael Kaufmann
Publisher : Springer
ISBN 13 : 3540449698
Total Pages : 325 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Drawing Graphs by : Michael Kaufmann

Download or read book Drawing Graphs written by Michael Kaufmann and published by Springer. This book was released on 2003-06-29 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph drawing comprises all aspects of visualizing structural relations between objects. The range of topics dealt with extends from graph theory, graph algorithms, geometry, and topology to visual languages, visual perception, and information visualization, and to computer-human interaction and graphics design. This monograph gives a systematic overview of graph drawing and introduces the reader gently to the state of the art in the area. The presentation concentrates on algorithmic aspects, with an emphasis on interesting visualization problems with elegant solutions. Much attention is paid to a uniform style of writing and presentation, consistent terminology, and complementary coverage of the relevant issues throughout the 10 chapters. This tutorial is ideally suited as an introduction for newcomers to graph drawing. Ambitioned practitioners and researchers active in the area will find it a valuable source of reference and information.

Hands-On Graph Analytics with Neo4j

Author : Estelle Scifo
Publisher : Packt Publishing Ltd
ISBN 13 : 1839215666
Total Pages : 496 pages
Book Rating : 4.8/5 (392 download)

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Book Synopsis Hands-On Graph Analytics with Neo4j by : Estelle Scifo

Download or read book Hands-On Graph Analytics with Neo4j written by Estelle Scifo and published by Packt Publishing Ltd. This book was released on 2020-08-21 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learning Key FeaturesGet up and running with graph analytics with the help of real-world examplesExplore various use cases such as fraud detection, graph-based search, and recommendation systemsGet to grips with the Graph Data Science library with the help of examples, and use Neo4j in the cloud for effective application scalingBook Description Neo4j is a graph database that includes plugins to run complex graph algorithms. The book starts with an introduction to the basics of graph analytics, the Cypher query language, and graph architecture components, and helps you to understand why enterprises have started to adopt graph analytics within their organizations. You’ll find out how to implement Neo4j algorithms and techniques and explore various graph analytics methods to reveal complex relationships in your data. You’ll be able to implement graph analytics catering to different domains such as fraud detection, graph-based search, recommendation systems, social networking, and data management. You’ll also learn how to store data in graph databases and extract valuable insights from it. As you become well-versed with the techniques, you’ll discover graph machine learning in order to address simple to complex challenges using Neo4j. You will also understand how to use graph data in a machine learning model in order to make predictions based on your data. Finally, you’ll get to grips with structuring a web application for production using Neo4j. By the end of this book, you’ll not only be able to harness the power of graphs to handle a broad range of problem areas, but you’ll also have learned how to use Neo4j efficiently to identify complex relationships in your data. What you will learnBecome well-versed with Neo4j graph database building blocks, nodes, and relationshipsDiscover how to create, update, and delete nodes and relationships using Cypher queryingUse graphs to improve web search and recommendationsUnderstand graph algorithms such as pathfinding, spatial search, centrality, and community detectionFind out different steps to integrate graphs in a normal machine learning pipelineFormulate a link prediction problem in the context of machine learningImplement graph embedding algorithms such as DeepWalk, and use them in Neo4j graphsWho this book is for This book is for data analysts, business analysts, graph analysts, and database developers looking to store and process graph data to reveal key data insights. This book will also appeal to data scientists who want to build intelligent graph applications catering to different domains. Some experience with Neo4j is required.

Bond Graph Methodology

Author : Wolfgang Borutzky
Publisher : Springer
ISBN 13 : 9781447157755
Total Pages : 0 pages
Book Rating : 4.1/5 (577 download)

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Book Synopsis Bond Graph Methodology by : Wolfgang Borutzky

Download or read book Bond Graph Methodology written by Wolfgang Borutzky and published by Springer. This book was released on 2014-11-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, engineering systems are of ever-increasing complexity and must be c- sidered asmultidisciplinary systems composed of interacting subsystems or system components from different engineering disciplines. Thus, an integration of various engineering disciplines, e.g, mechanical, electrical and control engineering in ac- current design approach is required. With regard to the systematic development and analysis of system models,interdisciplinary computer aided methodologies are - coming more and more important. A graphical description formalism particularly suited for multidisciplinary s- tems arebondgraphs devised by Professor Henry Paynter in as early as 1959 at the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts, USA and in use since then all over the world. This monograph is devoted exclusively to the bond graph methodology. It gives a comprehensive, in-depth, state-of-the-art presentation including recent results sc- tered over research articles and dissertations and research contributions by the - thor to a number of topics. The book systematically covers the fundamentals of developing bond graphs and deriving mathematical models from them, the recent developments in meth- ology, symbolic and numerical processing of mathematical models derived from bond graphs. Additionally it discusses modern modelling languages, the paradigm of object-oriented modelling, modern software that can be used for building and for processing of bond graph models, and provides a chapter with small case studies illustrating various applications of the methodology.

Bond Graph Modelling of Engineering Systems

Author : Wolfgang Borutzky
Publisher : Springer Science & Business Media
ISBN 13 : 1441993681
Total Pages : 446 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Bond Graph Modelling of Engineering Systems by : Wolfgang Borutzky

Download or read book Bond Graph Modelling of Engineering Systems written by Wolfgang Borutzky and published by Springer Science & Business Media. This book was released on 2011-06-01 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author presents current work in bond graph methodology by providing a compilation of contributions from experts across the world that covers theoretical topics, applications in various areas as well as software for bond graph modeling. It addresses readers in academia and in industry concerned with the analysis of multidisciplinary engineering systems or control system design who are interested to see how latest developments in bond graph methodology with regard to theory and applications can serve their needs in their engineering fields. This presentation of advanced work in bond graph modeling presents the leading edge of research in this field. It is hoped that it stimulates new ideas with regard to further progress in theory and in applications.

Graph-Theoretic Concepts in Computer Science

Author : Martin Charles Golumbic
Publisher : Springer
ISBN 13 : 3642346111
Total Pages : 357 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Graph-Theoretic Concepts in Computer Science by : Martin Charles Golumbic

Download or read book Graph-Theoretic Concepts in Computer Science written by Martin Charles Golumbic and published by Springer. This book was released on 2012-10-22 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 38th International Workshop on Graph Theoretic Concepts in Computer Science (WG 2012) held in Jerusalem, Israel on June 26-28, 2012. The 29 revised full papers presented were carefully selected and reviewed from 78 submissions. The papers are solicited describing original results on all aspects of graph-theoretic concepts in Computer Science, e.g. structural graph theory, sequential, parallel, randomized, parameterized, and distributed graph and network algorithms and their complexity, graph grammars and graph rewriting systems, graph-based modeling, graph-drawing and layout, random graphs, diagram methods, and support of these concepts by suitable implementations. The scope of WG includes all applications of graph-theoretic concepts in Computer Science, including data structures, data bases, programming languages, computational geometry, tools for software construction, communications, computing on the web, models of the web and scale-free networks, mobile computing, concurrency, computer architectures, VLSI, artificial intelligence, graphics, CAD, operations research, and pattern recognition

Graph Based Multimedia Analysis

Author : Ananda S Chowdhury
Publisher : Elsevier
ISBN 13 : 0443214867
Total Pages : 368 pages
Book Rating : 4.4/5 (432 download)

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Book Synopsis Graph Based Multimedia Analysis by : Ananda S Chowdhury

Download or read book Graph Based Multimedia Analysis written by Ananda S Chowdhury and published by Elsevier. This book was released on 2024-08-07 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph Based Multimedia Analysis applies concepts from graph theory to the problems of analyzing overabundant video data. Video data can be quite diverse: exocentric (captured by a standard camera) or egocentric (captured by a wearable device like Google Glass); of various durations (ranging from a few seconds to several hours); and could be from a single source or multiple sources. Efficient extraction of important information from such a large class of diverse video data can be overwhelming. The book, with its rich repertoire of theoretically elegant solutions, from graph theory in conjunction with deep learning, constrained optimization, and game theory, empowers the audience to achieve tasks like obtaining concise yet useful summaries and precisely recognizing single as well as multiple actions in a computationally efficient manner. The book provides a unique treatise on topics like egocentric video analysis and scalable video processing. - Addresses a number of challenging state-of-the-art problems in multimedia analysis like summarization, co-summarization, and action recognition - Handles a wide class of video with different genres, durations, and numbers - Applies a class of theoretically rich algorithms from the discipline of graph theory, in conjunction with deep learning, constrained optimization and game theory - Includes thorough complexity analyses of the proposed solutions, and an appendix containing implementable source codes

Graph Machine Learning

Author : Claudio Stamile
Publisher : Packt Publishing Ltd
ISBN 13 : 1800206755
Total Pages : 338 pages
Book Rating : 4.8/5 (2 download)

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Book Synopsis Graph Machine Learning by : Claudio Stamile

Download or read book Graph Machine Learning written by Claudio Stamile and published by Packt Publishing Ltd. This book was released on 2021-06-25 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build machine learning algorithms using graph data and efficiently exploit topological information within your models Key Features Implement machine learning techniques and algorithms in graph data Identify the relationship between nodes in order to make better business decisions Apply graph-based machine learning methods to solve real-life problems Book Description Graph Machine Learning will introduce you to a set of tools used for processing network data and leveraging the power of the relation between entities that can be used for predictive, modeling, and analytics tasks. The first chapters will introduce you to graph theory and graph machine learning, as well as the scope of their potential use. You'll then learn all you need to know about the main machine learning models for graph representation learning: their purpose, how they work, and how they can be implemented in a wide range of supervised and unsupervised learning applications. You'll build a complete machine learning pipeline, including data processing, model training, and prediction in order to exploit the full potential of graph data. After covering the basics, you'll be taken through real-world scenarios such as extracting data from social networks, text analytics, and natural language processing (NLP) using graphs and financial transaction systems on graphs. You'll also learn how to build and scale out data-driven applications for graph analytics to store, query, and process network information, and explore the latest trends on graphs. By the end of this machine learning book, you will have learned essential concepts of graph theory and all the algorithms and techniques used to build successful machine learning applications. What you will learn Write Python scripts to extract features from graphs Distinguish between the main graph representation learning techniques Learn how to extract data from social networks, financial transaction systems, for text analysis, and more Implement the main unsupervised and supervised graph embedding techniques Get to grips with shallow embedding methods, graph neural networks, graph regularization methods, and more Deploy and scale out your application seamlessly Who this book is for This book is for data scientists, data analysts, graph analysts, and graph professionals who want to leverage the information embedded in the connections and relations between data points to boost their analysis and model performance using machine learning. It will also be useful for machine learning developers or anyone who wants to build ML-driven graph databases. A beginner-level understanding of graph databases and graph data is required, alongside a solid understanding of ML basics. You'll also need intermediate-level Python programming knowledge to get started with this book.

Petri Nets in Science and Engineering

Author : Raul Campos-Rodriguez
Publisher : BoD – Books on Demand
ISBN 13 : 1789236924
Total Pages : 146 pages
Book Rating : 4.7/5 (892 download)

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Book Synopsis Petri Nets in Science and Engineering by : Raul Campos-Rodriguez

Download or read book Petri Nets in Science and Engineering written by Raul Campos-Rodriguez and published by BoD – Books on Demand. This book was released on 2018-09-19 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of chapters from different areas of science and engineering, where Petri Nets have been shown to be a useful tool for the design and modeling of the problems that arise in such fields. The areas covered in this book include manufacturing systems, authentication and cyber-security, computer architectures, mechanical systems, process mining, control theory and time analysis. The main focus of the chapters was to be illustrative, to help the development of intuitive ideas that may guide the reader to adopt Petri Nets in their scientific or engineering work. However, there are other chapters with deep mathematical basis such as time analysis. Whenever possible, models, graphics and examples illustrate the developed concepts.

Graph Neural Networks: Foundations, Frontiers, and Applications

Author : Lingfei Wu
Publisher : Springer Nature
ISBN 13 : 9811660549
Total Pages : 701 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Graph Neural Networks: Foundations, Frontiers, and Applications by : Lingfei Wu

Download or read book Graph Neural Networks: Foundations, Frontiers, and Applications written by Lingfei Wu and published by Springer Nature. This book was released on 2022-01-03 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning models are at the core of artificial intelligence research today. It is well known that deep learning techniques are disruptive for Euclidean data, such as images or sequence data, and not immediately applicable to graph-structured data such as text. This gap has driven a wave of research for deep learning on graphs, including graph representation learning, graph generation, and graph classification. The new neural network architectures on graph-structured data (graph neural networks, GNNs in short) have performed remarkably on these tasks, demonstrated by applications in social networks, bioinformatics, and medical informatics. Despite these successes, GNNs still face many challenges ranging from the foundational methodologies to the theoretical understandings of the power of the graph representation learning. This book provides a comprehensive introduction of GNNs. It first discusses the goals of graph representation learning and then reviews the history, current developments, and future directions of GNNs. The second part presents and reviews fundamental methods and theories concerning GNNs while the third part describes various frontiers that are built on the GNNs. The book concludes with an overview of recent developments in a number of applications using GNNs. This book is suitable for a wide audience including undergraduate and graduate students, postdoctoral researchers, professors and lecturers, as well as industrial and government practitioners who are new to this area or who already have some basic background but want to learn more about advanced and promising techniques and applications.