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Author : Jelena Klisara
Publisher :
ISBN 13 :
Total Pages : 139 pages
Book Rating : 4.:/5 (965 download)
Download or read book Graph-theoretic Approach to the Analysis of Complex Networks written by Jelena Klisara and published by . This book was released on 2016 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Matthias Dehmer
Publisher : Springer Science & Business Media
ISBN 13 : 0817649042
Total Pages : 409 pages
Book Rating : 4.8/5 (176 download)
Download or read book Towards an Information Theory of Complex Networks written by Matthias Dehmer and published by Springer Science & Business Media. This book was released on 2011-08-26 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: For over a decade, complex networks have steadily grown as an important tool across a broad array of academic disciplines, with applications ranging from physics to social media. A tightly organized collection of carefully-selected papers on the subject, Towards an Information Theory of Complex Networks: Statistical Methods and Applications presents theoretical and practical results about information-theoretic and statistical models of complex networks in the natural sciences and humanities. The book's major goal is to advocate and promote a combination of graph-theoretic, information-theoretic, and statistical methods as a way to better understand and characterize real-world networks. This volume is the first to present a self-contained, comprehensive overview of information-theoretic models of complex networks with an emphasis on applications. As such, it marks a first step toward establishing advanced statistical information theory as a unified theoretical basis of complex networks for all scientific disciplines and can serve as a valuable resource for a diverse audience of advanced students and professional scientists. While it is primarily intended as a reference for research, the book could also be a useful supplemental graduate text in courses related to information science, graph theory, machine learning, and computational biology, among others.
Author : Matthias Dehmer
Publisher : Springer Science & Business Media
ISBN 13 : 0817647899
Total Pages : 493 pages
Book Rating : 4.8/5 (176 download)
Download or read book Structural Analysis of Complex Networks written by Matthias Dehmer and published by Springer Science & Business Media. This book was released on 2010-10-14 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science, machine learning, artificial intelligence, computational and systems biology, cognitive science, computational linguistics, and mathematical chemistry. It may also be used as a supplementary textbook in graduate-level seminars on structural graph analysis, complex networks, or network-based machine learning methods.
Author : Piet van Mieghem
Publisher : Cambridge University Press
ISBN 13 : 1139492276
Total Pages : 363 pages
Book Rating : 4.1/5 (394 download)
Download or read book Graph Spectra for Complex Networks written by Piet van Mieghem and published by Cambridge University Press. This book was released on 2010-12-02 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyzing 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.
Author : Maarten van Steen
Publisher : Maarten Van Steen
ISBN 13 : 9789081540612
Total Pages : 285 pages
Book Rating : 4.5/5 (46 download)
Download or read book Graph Theory and Complex Networks written by Maarten van Steen and published by Maarten Van Steen. This book was released on 2010 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to explain the basics of graph theory that are needed at an introductory level for students in computer or information sciences. To motivate students and to show that even these basic notions can be extremely useful, the book also aims to provide an introduction to the modern field of network science. Mathematics is often unnecessarily difficult for students, at times even intimidating. For this reason, explicit attention is paid in the first chapters to mathematical notations and proof techniques, emphasizing that the notations form the biggest obstacle, not the mathematical concepts themselves. This approach allows to gradually prepare students for using tools that are necessary to put graph theory to work: complex networks. In the second part of the book the student learns about random networks, small worlds, the structure of the Internet and the Web, peer-to-peer systems, and social networks. Again, everything is discussed at an elementary level, but such that in the end students indeed have the feeling that they: 1.Have learned how to read and understand the basic mathematics related to graph theory. 2.Understand how basic graph theory can be applied to optimization problems such as routing in communication networks. 3.Know a bit more about this sometimes mystical field of small worlds and random networks. There is an accompanying web site www.distributed-systems.net/gtcn from where supplementary material can be obtained, including exercises, Mathematica notebooks, data for analyzing graphs, and generators for various complex networks.
Author : Horst Bunke
Publisher : Springer Science & Business Media
ISBN 13 : 0817645195
Total Pages : 230 pages
Book Rating : 4.8/5 (176 download)
Download or read book A Graph-Theoretic Approach to Enterprise Network Dynamics written by Horst Bunke and published by Springer Science & Business Media. This book was released on 2007-04-05 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph treats the application of numerous graph-theoretic algorithms to a comprehensive analysis of dynamic enterprise networks. Network dynamics analysis yields valuable information about network performance, efficiency, fault prediction, cost optimization, indicators and warnings. Based on many years of applied research on generic network dynamics, this work covers a number of elegant applications (including many new and experimental results) of traditional graph theory algorithms and techniques to computationally tractable network dynamics analysis to motivate network analysts, practitioners and researchers alike.
Author : Matthias Dehmer
Publisher : John Wiley & Sons
ISBN 13 : 3527627995
Total Pages : 480 pages
Book Rating : 4.5/5 (276 download)
Download or read book Analysis of Complex Networks written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2009-07-10 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical problems such as graph theory problems are of increasing importance for the analysis of modelling data in biomedical research such as in systems biology, neuronal network modelling etc. This book follows a new approach of including graph theory from a mathematical perspective with specific applications of graph theory in biomedical and computational sciences. The book is written by renowned experts in the field and offers valuable background information for a wide audience.
Author : Katharina A. Zweig
Publisher : Springer Science & Business Media
ISBN 13 : 3709107415
Total Pages : 546 pages
Book Rating : 4.7/5 (91 download)
Download or read book Network Analysis Literacy written by Katharina A. Zweig and published by Springer Science & Business Media. This book was released on 2016-10-26 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a perspective of network analysis as a tool to find and quantify significant structures in the interaction patterns between different types of entities. Moreover, network analysis provides the basic means to relate these structures to properties of the entities. It has proven itself to be useful for the analysis of biological and social networks, but also for networks describing complex systems in economy, psychology, geography, and various other fields. Today, network analysis packages in the open-source platform R and other open-source software projects enable scientists from all fields to quickly apply network analytic methods to their data sets. Altogether, these applications offer such a wealth of network analytic methods that it can be overwhelming for someone just entering this field. This book provides a road map through this jungle of network analytic methods, offers advice on how to pick the best method for a given network analytic project, and how to avoid common pitfalls. It introduces the methods which are most often used to analyze complex networks, e.g., different global network measures, types of random graph models, centrality indices, and networks motifs. In addition to introducing these methods, the central focus is on network analysis literacy – the competence to decide when to use which of these methods for which type of question. Furthermore, the book intends to increase the reader's competence to read original literature on network analysis by providing a glossary and intensive translation of formal notation and mathematical symbols in everyday speech. Different aspects of network analysis literacy – understanding formal definitions, programming tasks, or the analysis of structural measures and their interpretation – are deepened in various exercises with provided solutions. This text is an excellent, if not the best starting point for all scientists who want to harness the power of network analysis for their field of expertise.
Author : Meghanathan, Natarajan
Publisher : IGI Global
ISBN 13 : 1522528156
Total Pages : 376 pages
Book Rating : 4.5/5 (225 download)
Download or read book Graph Theoretic Approaches for Analyzing Large-Scale Social Networks written by Meghanathan, Natarajan and published by IGI Global. This book was released on 2017-07-13 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social network analysis has created novel opportunities within the field of data science. The complexity of these networks requires new techniques to optimize the extraction of useful information. Graph Theoretic Approaches for Analyzing Large-Scale Social Networks is a pivotal reference source for the latest academic research on emerging algorithms and methods for the analysis of social networks. Highlighting a range of pertinent topics such as influence maximization, probabilistic exploration, and distributed memory, this book is ideally designed for academics, graduate students, professionals, and practitioners actively involved in the field of data science.
Author : Ronald Dewayne Hagan
Publisher :
ISBN 13 :
Total Pages : 104 pages
Book Rating : 4.:/5 (11 download)
Download or read book Graph-theoretical Tools for the Analysis of Complex Networks written by Ronald Dewayne Hagan and published by . This book was released on 2017 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are currently experiencing an explosive growth in data collection technology that threatens to dwarf the commensurate gains in computational power predicted by Moore's Law. At the same time, researchers across numerous domain sciences are finding success using network models to represent their data. Graph algorithms are then applied to study the topological structure and tease out latent relationships between variables. Unfortunately, the problems of interest, such as finding dense subgraphs, are often the most difficult to solve from a computational point of view. Together, these issues motivate the need for novel algorithmic techniques in the study of graphs derived from large, complex, data sources. This dissertation describes the development and application of graph theoretic tools for the study of complex networks. Algorithms are presented that leverage efficient, exact solutions to difficult combinatorial problems for epigenetic biomarker detection and disease subtyping based on gene expression signatures. Extensive testing on publicly available data is presented supporting the efficacy of these approaches. To address efficient algorithm design, a study of the two core tenets of fixed parameter tractability (branching and kernelization) is considered in the context of a parallel implementation of vertex cover. Results of testing on a wide variety of graphs derived from both real and synthetic data are presented. It is shown that the relative success of kernelization versus branching is found to be largely dependent on the degree distribution of the graph. Throughout, an emphasis is placed upon the practicality of resulting implementations to advance the limits of effective computation.
Author : Matthias Dehmer
Publisher : CRC Press
ISBN 13 : 1315353598
Total Pages : 290 pages
Book Rating : 4.3/5 (153 download)
Download or read book Big Data of Complex Networks written by Matthias Dehmer and published by CRC Press. This book was released on 2016-08-19 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investigating large sets of complex networks. Intended for computer scientists, statisticians and mathematicians interested in the big data and networks, Big Data of Complex Networks is also a valuable tool for researchers in the fields of visualization, data analysis, computer vision and bioinformatics. Key features: Provides a complete discussion of both the hardware and software used to organize big data Describes a wide range of useful applications for managing big data and resultant data sets Maintains a firm focus on massive data and large networks Unveils innovative techniques to help readers handle big data Matthias Dehmer received his PhD in computer science from the Darmstadt University of Technology, Germany. Currently, he is Professor at UMIT – The Health and Life Sciences University, Austria, and the Universität der Bundeswehr München. His research interests are in graph theory, data science, complex networks, complexity, statistics and information theory. Frank Emmert-Streib received his PhD in theoretical physics from the University of Bremen, and is currently Associate professor at Tampere University of Technology, Finland. His research interests are in the field of computational biology, machine learning and network medicine. Stefan Pickl holds a PhD in mathematics from the Darmstadt University of Technology, and is currently a Professor at Bundeswehr Universität München. His research interests are in operations research, systems biology, graph theory and discrete optimization. Andreas Holzinger received his PhD in cognitive science from Graz University and his habilitation (second PhD) in computer science from Graz University of Technology. He is head of the Holzinger Group HCI-KDD at the Medical University Graz and Visiting Professor for Machine Learning in Health Informatics Vienna University of Technology.
Author : Ernesto Estrada
Publisher : Oxford University Press
ISBN 13 : 019959175X
Total Pages : 478 pages
Book Rating : 4.1/5 (995 download)
Download or read book The Structure of Complex Networks written by Ernesto Estrada and published by Oxford University Press. This book was released on 2012 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book integrates approaches from mathematics, physics and computer sciences to analyse the organisation of complex networks. Every organisational principle of networks is defined, quantified and then analysed for its influences on the properties and functions of molecular, biological, ecological and social networks.
Author : Jörg Reichardt
Publisher : Springer
ISBN 13 : 3540878335
Total Pages : 162 pages
Book Rating : 4.5/5 (48 download)
Download or read book Structure in Complex Networks written by Jörg Reichardt and published by Springer. This book was released on 2008-11-04 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the modern world of gigantic datasets, which scientists and practioners of all fields of learning are confronted with, the availability of robust, scalable and easy-to-use methods for pattern recognition and data mining are of paramount importance, so as to be able to cope with the avalanche of data in a meaningful way. This concise and pedagogical research monograph introduces the reader to two specific aspects - clustering techniques and dimensionality reduction - in the context of complex network analysis. The first chapter provides a short introduction into relevant graph theoretical notation; chapter 2 then reviews and compares a number of cluster definitions from different fields of science. In the subsequent chapters, a first-principles approach to graph clustering in complex networks is developed using methods from statistical physics and the reader will learn, that even today, this field significantly contributes to the understanding and resolution of the related statistical inference issues. Finally, an application chapter examines real-world networks from the economic realm to show how the network clustering process can be used to deal with large, sparse datasets where conventional analyses fail.
Author : Mehran Mesbahi
Publisher : Princeton University Press
ISBN 13 : 1400835356
Total Pages : 424 pages
Book Rating : 4.4/5 (8 download)
Download or read book Graph Theoretic Methods in Multiagent Networks written by Mehran Mesbahi and published by Princeton University Press. This book was released on 2010-07-01 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 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
Author : Fan R. K. Chung
Publisher : American Mathematical Soc.
ISBN 13 : 0821836579
Total Pages : 274 pages
Book Rating : 4.8/5 (218 download)
Download or read book Complex Graphs and Networks written by Fan R. K. Chung and published by American Mathematical Soc.. This book was released on 2006 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph theory is a primary tool for detecting numerous hidden structures in various information networks, including Internet graphs, social networks, biological networks, or any graph representing relations in massive data sets. This book explains the universal and ubiquitous coherence in the structure of these realistic but complex networks.
Author : Hocine Cherifi
Publisher : Cambridge Scholars Publishing
ISBN 13 : 1443863246
Total Pages : 355 pages
Book Rating : 4.4/5 (438 download)
Download or read book Complex Networks and their Applications written by Hocine Cherifi and published by Cambridge Scholars Publishing. This book was released on 2014-06-30 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuelled by the big data paradigm, the study of networks is an interdisciplinary field that is growing at the interface of many branches of science including mathematics, physics, computer science, biology, economics and the social sciences. This book, written by experts from the Network Science community, covers a wide range of theoretical and practical advances in this highly active field, highlighting the strong interconnections between works in different disciplines. The eleven chapters take the reader through the essential concepts for the structural analysis of networks, and their applications to real-world scenarios. Being self-contained, the book is intended for researchers, graduate and advanced undergraduate students from different intellectual backgrounds. Each chapter combines mathematical rigour with rich references to the literature, while remaining accessible to a wide range of readers who wish to understand some of the key issues encountered in many aspects of networked everyday life.
Author : Guido Caldarelli
Publisher : EOLSS Publications
ISBN 13 : 1848263228
Total Pages : 362 pages
Book Rating : 4.8/5 (482 download)
Download or read book Complex Networks written by Guido Caldarelli and published by EOLSS Publications. This book was released on 2010-11-30 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of complex network exploded since the 1990s, the number of publications in a variety of different areas has grown exponentially and practically, and every discipline started to recognize the presence of these mathematical structures in its area of research. Actually almost any system from the nowadays traditional example of the Internet to complex patterns of metabolic reactions can be analyzed through the graph theory. In its simplest and non rigorous definition a graph is a mathematical object consisting of a set of elements (vertices) and a series of links between these vertices (edges). This is of course a very general description, and as any mathematical abstraction, the idea is to discard many of the particular properties of the phenomenon studied. Nevertheless, this modeling is remarkably accurate for a variety of situations. Vertices can be persons related by friendship or acquaintances relations. Vertices can be proteins connected with one another if they interact in the cell. Networks have always existed in Nature of course, but it is fair to say that given the present technological explosion, they became more and more important. Starting from the Internet the web of connections between computers we started to link and share our documents through web applications and we start to get connected with a number of persons larger than usual. It is this revolution in our daily habit that made natural thinking of networks in science and research. Once this has been realized it became natural to see the cell as a network of molecular events from chemical reactions to gene expressions. The point is to establish if this new perspective can help researchers in finding new results and by understanding the development of these phenomena and possibly control their evolution. We believe that this is the case and in the following we shall provide the evidence of that. Together with applications there are of course true scientific questions attached to network theory. Consider the various ways in which the edges are distributed among the vertices: even by keeping the number of edges and vertices constant we have many different patterns possible. Interestingly some features used to describe these shapes are not related to the particular example considered, but instead they are universal. That is to say they can be found in almost any network around. In this book, we introduce the subject of complex networks and we present the structure of the associated topics that range from social science to biology and finance. We start by considering the mathematical foundations of networks and we then move to an overview of the various applications
