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Graph Drawing and Network Visualization
by Yifan Hu Martin NöllenburgThis book constitutes revised selected papers from the 24th International Symposium on Graph Drawing and Network Visualization, GD 2016, held in Athens, Greece, in September 2016. The 45 papers presented in this volume were carefully reviewed and selected from 99 submissions. They were organized in topical sections named: large graphs and clutter avoidance; clustered graphs; planar graphs, layered and tree drawings; visibility representations; beyond planarity; crossing minimization and crossing numbers; topological graph theory; special graph embeddings; dynamic graphs, contest report.
Graph Energy
by Xueliang Li Ivan Gutman Yongtang ShiThis book is about graph energy. The authors have included many of the important results on graph energy, such as the complete solution to the conjecture on maximal energy of unicyclic graphs, the Wagner-Heuberger's result on the energy of trees, the energy of random graphs or the approach to energy using singular values. It contains an extensive coverage of recent results and a gradual development of topics and the inclusion of complete proofs from most of the important recent results in the area. The latter fact makes it a valuable reference for researchers looking to get into the field of graph energy, further stimulating it with occasional inclusion of open problems. The book provides a comprehensive survey of all results and common proof methods obtained in this field with an extensive reference section. The book is aimed mainly towards mathematicians, both researchers and doctoral students, with interest in the field of mathematical chemistry.
Graph Learning and Network Science for Natural Language Processing (Computational Intelligence Techniques)
by Muskan Garg, Amit Kumar Gupta and Rajesh PrasadAdvances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method. This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL. It also contains information about language generation based on graphical theories and language models. Features: -Presents a comprehensive study of the interdisciplinary graphical approach to NLP -Covers recent computational intelligence techniques for graph-based neural network models -Discusses advances in random walk-based techniques, semantic webs, and lexical networks -Explores recent research into NLP for graph-based streaming data -Reviews advances in knowledge graph embedding and ontologies for NLP approaches This book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.
Graph Neural Network for Feature Extraction and Classification of Hyperspectral Remote Sensing Images (Intelligent Perception and Information Processing)
by Yao Ding Zhili Zhang Haojie Hu Fang He Shuli Cheng Yijun ZhangThis book deals with hyperspectral image classification using graph neural network methods, focusing on classification model designing, graph information dissemination, and graph construction. In the book, various graph neural network based classifiers have been proposed for hyperspectral image classification to improve the classification accuracy. This book has promoted the application of graph neural network in hyperspectral image classification, providing reference for remote sensing image processing. It will be a useful reference for researchers in remote sensing image processing and image neural network design.
Graph Neural Network Methods and Applications in Scene Understanding
by Weibin Liu Huaqing Hao Hui Wang Zhiyuan Zou Weiwei XingThe book focuses on graph neural network methods and applications for scene understanding. Graph Neural Network is an important method for graph-structured data processing, which has strong capability of graph data learning and structural feature extraction. Scene understanding is one of the research focuses in computer vision and image processing, which realizes semantic segmentation and object recognition of image or video. In this book, the algorithm, system design and performance evaluation of scene understanding based on graph neural networks have been studied. First, the book elaborates the background and basic concepts of graph neural network and scene understanding, then introduces the operation mechanism and key methodological foundations of graph neural network. The book then comprehensively explores the implementation and architectural design of graph neural networks for scene understanding tasks, including scene parsing, human parsing, and video object segmentation. The aim of this book is to provide timely coverage of the latest advances and developments in graph neural networks and their applications to scene understanding, particularly for readers interested in research and technological innovation in machine learning, graph neural networks and computer vision. Features of the book include self-supervised feature fusion based graph convolutional network is designed for scene parsing, structure-property based graph representation learning is developed for human parsing, dynamic graph convolutional network based on multi-label learning is designed for human parsing, and graph construction and graph neural network with transformer are proposed for video object segmentation.
Graph Polynomials (Discrete Mathematics and Its Applications)
by Yongtang Shi; Matthias Dehmer; Xueliang Li; Ivan GutmanThis book covers both theoretical and practical results for graph polynomials. Graph polynomials have been developed for measuring combinatorial graph invariants and for characterizing graphs. Various problems in pure and applied graph theory or discrete mathematics can be treated and solved efficiently by using graph polynomials. Graph polynomials have been proven useful areas such as discrete mathematics, engineering, information sciences, mathematical chemistry and related disciplines.
Graph Sampling
by Li-Chun ZhangMany technological, socio-economic, environmental, biomedical phenomena exhibit an underlying graph structure. Valued graph allows one to incorporate the connections or links among the population units in addition. The links may provide effectively access to the part of population that is the primary target, which is the case for many unconventional sampling methods, such as indirect, network, line-intercept or adaptive cluster sampling. Or, one may be interested in the structure of the connections, in terms of the corresponding graph properties or parameters, such as when various breadth- or depth-first non-exhaustive search algorithms are applied to obtain compressed views of large often dynamic graphs. Graph sampling provides a statistical approach to study real graphs from either of these perspectives. It is based on exploring the variation over all possible sample graphs (or subgraphs) which can be taken from the given population graph, by means of the relevant known sampling probabilities. The resulting design-based inference is valid whatever the unknown properties of the given real graphs. One-of-a-kind treatise of multidisciplinary topics relevant to statistics, mathematics and data science. Probabilistic treatment of breadth-first and depth-first non-exhaustive search algorithms in graphs. Presenting cutting-edge theory and methods based on latest research. Pathfinding for future research on sampling from real graphs. Graph Sampling can primarily be used as a resource for researchers working with sampling or graph problems, and as the basis of an advanced course for post-graduate students in statistics, mathematics and data science.
Graph Spectra for Complex Networks
by Piet Van MieghemAnalyzing the behavior of complex networks is an important element in the design of new man-made structures such as communication systems and biologically engineered molecules. Because any complex network can be represented by a graph, and therefore in turn by a matrix, graph theory has become a powerful tool in the investigation of network performance. This self-contained 2010 book provides a concise introduction to the theory of graph spectra and its applications to the study of complex networks. Covering a range of types of graphs and topics important to the analysis of complex systems, this guide provides the mathematical foundation needed to understand and apply spectral insight to real-world systems. In particular, the general properties of both the adjacency and Laplacian spectrum of graphs are derived and applied to complex networks. An ideal resource for researchers and students in communications networking as well as in physics and mathematics.
Graph Structure and Monadic Second-Order Logic
by Bruno Courcelle Joost EngelfrietThe study of graph structure has advanced in recent years with great strides: finite graphs can be described algebraically, enabling them to be constructed out of more basic elements. Separately the properties of graphs can be studied in a logical language called monadic second-order logic. In this book, these two features of graph structure are brought together for the first time in a presentation that unifies and synthesizes research over the last 25 years. The authors not only provide a thorough description of the theory, but also detail its applications, on the one hand to the construction of graph algorithms, and, on the other to the extension of formal language theory to finite graphs. Consequently the book will be of interest to graduate students and researchers in graph theory, finite model theory, formal language theory, and complexity theory.
Graph Structures for Knowledge Representation and Reasoning: 6th International Workshop, GKR 2020, Virtual Event, September 5, 2020, Revised Selected Papers (Lecture Notes in Computer Science #12640)
by Michael Cochez Madalina Croitoru Pierre Marquis Sebastian RudolphThis open access book constitutes the thoroughly refereed post-conference proceedings of the 6th International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2020, held virtually in September 2020, associated with ECAI 2020, the 24th European Conference on Artificial Intelligence.The 7 revised full papers presented together with 2 invited contributions were reviewed and selected from 9 submissions. The contributions address various issues for knowledge representation and reasoning and the common graph-theoretic background, which allows to bridge the gap between the different communities.
Graph-Theoretic Concepts in Computer Science: 46th International Workshop, WG 2020, Leeds, UK, June 24–26, 2020, Revised Selected Papers (Lecture Notes in Computer Science #12301)
by Isolde Adler Haiko MüllerThis book constitutes the revised papers of the 46th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2020, held in Leeds, UK, in June 2020. The workshop was held virtually due to the COVID-19 pandemic. The 32 full papers presented in this volume were carefully reviewed and selected from 94 submissions. They cover a wide range of areas, aiming to present emerging research results and to identify and explore directions of future research of concepts on graph theory and how they can be applied to various areas in computer science.
Graph-Theoretic Concepts in Computer Science
by Hans L. Bodlaender Gerhard J. WoegingerThe 29th International Workshop on Graph-Theoretic Concepts in Computer Science(WG2003)washeldintheMennorodeconferenceCenterinElspeet,The Netherlands. TheworkshopwasorganizedbytheCenterforAlgorithmicSystems of the Institute of Information and Computing Sciences of Utrecht University. The workshop took place June 19-21, 2003. The 72 participants of WG 2003 came from universities and research institutes from 18 di?erent countries and ?ve di?erent continents. The workshop looks back at a long tradition. It was ?rst held in 1975, and has been held 20 times in Germany, twice in Austria, and once in Italy, Slo- kia, Switzerland, and the Czech Republic, and has now been held for the third time in The Netherlands. The workshop aims at uniting theory and practice by demonstrating how graph-theoretic concepts can be applied to various areas in computerscience,orbyextractingnewproblemsfromapplications. Itisdevoted to the theoretical and practical aspects of graph concepts in computer science. The goal is to present recent research results and to identify and explore - rections of future research. The talks given at the workshop showed how recent research results from algorithmic graph theory can be used in computer science and which graph-theoretic questions arise from new developments in computer science.
Graph-Theoretic Concepts in Computer Science
by Pinar HeggernesThis book constitutes revised selected papers from the 42nd International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2016, held in Istanbul, Turkey, in June 2016. The 25 papers presented in this volume were carefully reviewed and selected from 74 submissions. The WG conferences aim to connect theory and practice by demonstrating how graph-theoretic concepts can be applied to various areas of computer science and by extracting new graph problems from applications. Their goal is to present new research results and to identify and explore directions of future research.
Graph-Theoretic Concepts in Computer Science: 47th International Workshop, WG 2021, Warsaw, Poland, June 23–25, 2021, Revised Selected Papers (Lecture Notes in Computer Science #12911)
by Łukasz Kowalik Michał Pilipczuk Paweł RzążewskiThis book constitutes the proceedings of the 47th International Workshop on Graph-Theoretic Concepts in Computer Science which was held during June 23–25, 2021. The conference was planned to take place in Warsaw, Poland, but changed to an online event due to the COVID-19 pandemic. The 30 full papers included in this volume were carefully reviewed and selected from 73 submissions. The conference aims to merge theory and practice by demonstrating how concepts from graph theory can be applied to various areas in computer science or by extracting new graph-theoretic problems from applications.Chapter “Bears with Hats and Independence Polynomials” is are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Graph-Theoretic Concepts in Computer Science: 50th International Workshop, WG 2024, Gozd Martuljek, Slovenia, June 19–21, 2024, Revised Selected Papers (Lecture Notes in Computer Science #14760)
by Daniel Kráľ Martin MilaničThis book constitutes the refereed proceedings of the 50th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2024, held in Gozd Martuljek, Slovenia in June 2024, The 31 papers presented in this volume were carefully reviewed and selected from 89 submissions. Additionally, this volume also contains a survey on approximation algorithms for tree-width, path-width, and tree-depth prepared by Hans Bodlander, who delivered the Test of Time Award talk at WG 2024. The WG 2024 workshop aims to merge theory and practice by demonstrating how concepts from graph theory can be applied to various areas in computer science or by extracting new graph-theoretic problems from applications.
Graph-Theoretic Concepts in Computer Science
by Dieter Kratsch Ioan TodincaThis book constitutes the thoroughly refereed post-conference proceedings of the 40th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2014, held in Nouan-le-Fuzelier, France, in June 2014. The 32 revised full papers presented were carefully reviewed and selected from 80 submissions. The book also includes two invited papers. The papers cover a wide range of topics in graph theory related to computer science, such as design and analysis of sequential, parallel, randomized, parameterized and distributed graph and network algorithms; structural graph theory with algorithmic or complexity applications; computational complexity of graph and network problems; graph grammars, graph rewriting systems and graph modeling; graph drawing and layouts; computational geometry; random graphs and models of the web and scale-free networks; and support of these concepts by suitable implementations and applications.
Graph-Theoretic Concepts in Computer Science
by Ernst W. MayrThis volume presents the proceedings of the 20th International Workshop on Graph-Theoretic Concepts in Computer Science (WG '94), held in Herrsching, Germany in June 1994. The volume contains 32 thoroughly revised papers selected from 66 submissions and provides an up-to-date snapshot of the research performed in the field. The topics addressed are graph grammars, treewidth, special graph classes, algorithms on graphs, broadcasting and architecture, planar graphs and related problems, and special graph problems.
Graph-Theoretic Concepts in Computer Science: 49th International Workshop, WG 2023, Fribourg, Switzerland, June 28–30, 2023, Revised Selected Papers (Lecture Notes in Computer Science #14093)
by Daniël Paulusma Bernard RiesThis volume constitutes the thoroughly refereed proceedings of the 49th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2023. The 33 full papers presented in this volume were carefully reviewed and selected from a total of 116 submissions. The WG 2022 workshop aims to merge theory and practice by demonstrating how concepts from graph theory can be applied to various areas in computer science, or by extracting new graph theoretic problems from applications.
Graph-Theoretic Concepts in Computer Science: 45th International Workshop, WG 2019, Vall de Núria, Spain, June 19–21, 2019, Revised Papers (Lecture Notes in Computer Science #11789)
by Ignasi Sau Dimitrios M. ThilikosThis book constitutes the revised papers of the 45th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2019, held in Vall de Núria, Spain, in June 2019. The 29 full papers presented in this volume were carefully reviewed and selected from 87 submissions. They cover a wide range of areas, aiming at connecting theory and applications by demonstrating how graph-theoretic concepts can be applied in various areas of computer science. Another focus is on presenting recent results and on identifying and exploring promising directions of future research.
Graph Theoretic Methods in Multiagent Networks (Princeton Series in Applied Mathematics #33)
by Mehran Mesbahi Magnus EgerstedtThis accessible book provides an introduction to the analysis and design of dynamic multiagent networks. Such networks are of great interest in a wide range of areas in science and engineering, including: mobile sensor networks, distributed robotics such as formation flying and swarming, quantum networks, networked economics, biological synchronization, and social networks. Focusing on graph theoretic methods for the analysis and synthesis of dynamic multiagent networks, the book presents a powerful new formalism and set of tools for networked systems. The book's three sections look at foundations, multiagent networks, and networks as systems. The authors give an overview of important ideas from graph theory, followed by a detailed account of the agreement protocol and its various extensions, including the behavior of the protocol over undirected, directed, switching, and random networks. They cover topics such as formation control, coverage, distributed estimation, social networks, and games over networks. And they explore intriguing aspects of viewing networks as systems, by making these networks amenable to control-theoretic analysis and automatic synthesis, by monitoring their dynamic evolution, and by examining higher-order interaction models in terms of simplicial complexes and their applications. The book will interest graduate students working in systems and control, as well as in computer science and robotics. It will be a standard reference for researchers seeking a self-contained account of system-theoretic aspects of multiagent networks and their wide-ranging applications. This book has been adopted as a textbook at the following universities: ? University of Stuttgart, Germany Royal Institute of Technology, Sweden Johannes Kepler University, Austria Georgia Tech, USA University of Washington, USA Ohio University, USA
Graph-Theoretical Matrices in Chemistry
by null Dusanka Janezic null Ante Milicevic null Sonja Nikolic null Nenad TrinajsticGraph-Theoretical Matrices in Chemistry presents a systematic survey of graph-theoretical matrices and highlights their potential uses. This comprehensive volume is an updated, extended version of a former bestseller featuring a series of mathematical chemistry monographs. In this edition, nearly 200 graph-theoretical matrices are included.This sec
Graph Theory
by Ralucca Gera Stephen Hedetniemi Craig LarsonThis is the first in a series of volumes, which provide an extensive overview of conjectures and open problems in graph theory. The readership of each volume is geared toward graduate students who may be searching for research ideas. However, the well-established mathematician will find the overall exposition engaging and enlightening. Each chapter, presented in a story-telling style, includes more than a simple collection of results on a particular topic. Each contribution conveys the history, evolution, and techniques used to solve the authors' favorite conjectures and open problems, enhancing the reader's overall comprehension and enthusiasm. The editors were inspired to create these volumes by the popular and well attended special sessions, entitled "My Favorite Graph Theory Conjectures," which were held at the winter AMS/MAA Joint Meeting in Boston (January, 2012), the SIAM Conference on Discrete Mathematics in Halifax (June,2012) and the winter AMS/MAA Joint meeting in Baltimore(January, 2014). In an effort to aid in the creation and dissemination of open problems, which is crucial to the growth and development of a field, the editors requested the speakers, as well as notable experts in graph theory, to contribute to these volumes.
Graph Theory
by Ronald GouldThis introduction to graph theory focuses on well-established topics, covering primary techniques and including both algorithmic and theoretical problems. The algorithms are presented with a minimum of advanced data structures and programming details. This thoroughly corrected 1988 edition provides insights to computer scientists as well as advanced undergraduates and graduate students of topology, algebra, and matrix theory. Fundamental concepts and notation and elementary properties and operations are the first subjects, followed by examinations of paths and searching, trees, and networks. Subsequent chapters explore cycles and circuits, planarity, matchings, and independence. The text concludes with considerations of special topics and applications and extremal theory. Exercises appear throughout the text.
Graph Theory: An Interactive View (Dover Books on Mathematics #61)
by Frank HararyAn effort has been made to present the various topics in the theory of graphs in a logical order, to indicate the historical background, and to clarify the exposition by including figures to illustrate concepts and results. In addition, there are three appendices which provide diagrams of graphs, directed graphs, and trees. The emphasis throughout is on theorems rather than algorithms or applications, which however are occaisionally mentioned.
Graph Theory: Favorite Conjectures And Open Problems - 1 (Problem Books in Mathematics)
by Stephen T. Hedetniemi Teresa W. Haynes Ralucca GeraThis second volume in a two-volume series provides an extensive collection of conjectures and open problems in graph theory. It is designed for both graduate students and established researchers in discrete mathematics who are searching for research ideas and references. Each chapter provides more than a simple collection of results on a particular topic; it captures the reader’s interest with techniques that worked and failed in attempting to solve particular conjectures. The history and origins of specific conjectures and the methods of researching them are also included throughout this volume. Students and researchers can discover how the conjectures have evolved and the various approaches that have been used in an attempt to solve them. An annotated glossary of nearly 300 graph theory parameters, 70 conjectures, and over 600 references is also included in this volume. This glossary provides an understanding of parameters beyond their definitions and enables readers to discover new ideas and new definitions in graph theory. The editors were inspired to create this series of volumes by the popular and well-attended special sessions entitled “My Favorite Graph Theory Conjectures,” which they organized at past AMS meetings. These sessions were held at the winter AMS/MAA Joint Meeting in Boston, January 2012, the SIAM Conference on Discrete Mathematics in Halifax in June 2012, as well as the winter AMS/MAA Joint Meeting in Baltimore in January 2014, at which many of the best-known graph theorists spoke. In an effort to aid in the creation and dissemination of conjectures and open problems, which is crucial to the growth and development of this field, the editors invited these speakers, as well as other experts in graph theory, to contribute to this series.