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Visual Analysis Of Multilayer Networks
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Book Synopsis Visual Analysis of Multilayer Networks by : Fintan McGee
Download or read book Visual Analysis of Multilayer Networks written by Fintan McGee and published by Morgan & Claypool Publishers. This book was released on 2021-06-10 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an overview and structured analysis of contemporary multilayer network visualization. It surveys techniques as well as tools, tasks, and analytics from within application domains. It also identifies research opportunities and examines outstanding challenges along with potential solutions and future research directions for addressing them. Visual Analysis of Multilayer Networks is not only for visualization researchers, but for those who need to visualize multilayer networks in the domain of complex systems, as well as anyone solving problems within application domains. The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges. The multilayer network model recognizes that the complexity of relationships between entities in real-world systems is better embraced as several interdependent subsystems (or layers) rather than a simple graph approach. Despite only recently being formalized and defined, this model can be applied to problems in the domains of life sciences, sociology, digital humanities, and more. Within the domain of network visualization there already are many existing systems, which visualize data sets having many characteristics of multilayer networks, and many techniques, which are applicable to their visualization.
Book Synopsis Visual Analysis of Multilayer Networks by : Fintan McGee
Download or read book Visual Analysis of Multilayer Networks written by Fintan McGee and published by Springer Nature. This book was released on 2022-06-01 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges. The multilayer network model recognizes that the complexity of relationships between entities in real-world systems is better embraced as several interdependent subsystems (or layers) rather than a simple graph approach. Despite only recently being formalized and defined, this model can be applied to problems in the domains of life sciences, sociology, digital humanities, and more. Within the domain of network visualization there already are many existing systems, which visualize data sets having many characteristics of multilayer networks, and many techniques, which are applicable to their visualization. In this Synthesis Lecture, we provide an overview and structured analysis of contemporary multilayer network visualization. This is not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those solving problems within application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer network visualization, as well as tools, tasks, and analytic techniques from within application domains. We also identify the research opportunities and examine outstanding challenges for multilayer network visualization along with potential solutions and future research directions for addressing them.
Book Synopsis Multilayer Networks: Analysis and Visualization by : Manlio De Domenico
Download or read book Multilayer Networks: Analysis and Visualization written by Manlio De Domenico and published by Springer Nature. This book was released on 2022-03-31 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: The adoption of multilayer analysis techniques is rapidly expanding across all areas of knowledge, from social sciences (the first facing the complexity of such structures, decades ago) to computer science, from biology to engineering. However, until now, no book has dealt exclusively with the analysis and visualization of multilayer networks. Multilayer Networks: Analysis and Visualization provides a guided introduction to one of the most complete computational frameworks, named muxViz, with introductory information about the underlying theoretical aspects and a focus on the analytical side. Dozens of analytical scripts and examples to use the muxViz library in practice, by means of the Graphical User Interface or by means of the R scripting language, are provided. In addition to researchers in the field of network science, as well as practitioners interested in network visualization and analysis, this book will appeal to researchers without strong technical or computer science background who want to learn how to use muxViz software, such as researchers from humanities, social science and biology: audiences which are targeted by case studies included in the book. Other interdisciplinary audiences include computer science, physics, neuroscience, genetics, urban transport and engineering, digital humanities, social and computational social science. Readers will learn how to use, in a very practical way (i.e., without focusing on theoretical aspects), the algorithms developed by the community and implemented in the free and open-source software muxViz. The data used in the book is available on a dedicated (open and free) site.
Book Synopsis Multiplex Networks by : Emanuele Cozzo
Download or read book Multiplex Networks written by Emanuele Cozzo and published by Springer. This book was released on 2018-06-27 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the basis of a formal language and explores its possibilities in the characterization of multiplex networks. Armed with the formalism developed, the authors define structural metrics for multiplex networks. A methodology to generalize monoplex structural metrics to multiplex networks is also presented so that the reader will be able to generalize other metrics of interest in a systematic way. Therefore, this book will serve as a guide for the theoretical development of new multiplex metrics. Furthermore, this Brief describes the spectral properties of these networks in relation to concepts from algebraic graph theory and the theory of matrix polynomials. The text is rounded off by analyzing the different structural transitions present in multiplex systems as well as by a brief overview of some representative dynamical processes. Multiplex Networks will appeal to students, researchers, and professionals within the fields of network science, graph theory, and data science.
Book Synopsis Multilayer Social Networks by : Mark E. Dickison
Download or read book Multilayer Social Networks written by Mark E. Dickison and published by Cambridge University Press. This book was released on 2016-07-19 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book unifies and consolidates methods for analyzing multilayer networks arising from the social and physical sciences and computing.
Book Synopsis Animal Social Networks by : Dr. Jens Krause
Download or read book Animal Social Networks written by Dr. Jens Krause and published by Oxford University Press. This book was released on 2015 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scientific study of networks - computer, social, and biological - has received an enormous amount of interest in recent years. However, the network approach has been applied to the field of animal behaviour relatively late compared to many other biological disciplines. Understanding social network structure is of great importance for biologists since the structural characteristics of any network will affect its constituent members and influence a range of diverse behaviours. These include finding and choosing a sexual partner, developing and maintaining cooperative relationships, and engaging in foraging and anti-predator behavior. This novel text provides an overview of the insights that network analysis has provided into major biological processes, and how it has enhanced our understanding of the social organisation of several important taxonomic groups. It brings together researchers from a wide range of disciplines with the aim of providing both an overview of the power of the network approach for understanding patterns and process in animal populations, as well as outlining how current methodological constraints and challenges can be overcome. Animal Social Networks is principally aimed at graduate level students and researchers in the fields of ecology, zoology, animal behaviour, and evolutionary biology but will also be of interest to social scientists.
Book Synopsis Complex Systems, Smart Territories and Mobility by : Patricia Sajous
Download or read book Complex Systems, Smart Territories and Mobility written by Patricia Sajous and published by Springer Nature. This book was released on 2021-01-27 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reflects the outcome of contribution by the plural community and of the interactions between disciplines. With the mass of data available through Information and Communication Technologies (ICT) in an unprecedented quantity since the Human History, it is now possible to access dimensions of knowledge that, though not hidden, could not be grasped in the same way in the past. The question of how this information can be used for the benefit of institutional and economic actors to foster the development of a territory. Tackling the issue from a resolutely interdisciplinary perspective, the authors explore the theories and methods of complex systems in order to discuss how they can contribute in these new circumstances to territorial intelligence and to the development practices in which it is embodied. This book illustrates how today’s research explores the multiple facets of territorial systems in order to reproduce their richness. It invites readers to learn about the challenges, ideas, results and advances present in this domain.
Book Synopsis The Power of Corporate Networks by : Thomas David
Download or read book The Power of Corporate Networks written by Thomas David and published by Routledge. This book was released on 2014-08-27 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Corporate networks, the links between companies and their leaders, reflect a country’s economic organization and its corporate governance system. Most research on corporate networks focuses on individual countries or particular time periods, however, making fruitful comparisons over longer periods of time difficult. This book provides a unique long-term analysis of the rise, consolidation, decline, and occasional re-emergence of these networks in fourteen countries across North and South America, Europe, and Asia in the 20th and early 21st centuries. In this volume, the editors bring together the most internationally well-known specialists to investigate the long-term development of corporate networks. Using a combination of quantitative and qualitative research approaches, the authors describe the main developments and changes in the corporate network over time by focusing on important network indicators in benchmark years, and identify historical explanations for these developments. This unique, long-term perspective allows readers insight into how and why national corporate networks have evolved over time.
Book Synopsis Neural Networks for Perception by : Harry Wechsler
Download or read book Neural Networks for Perception written by Harry Wechsler and published by Academic Press. This book was released on 2014-05-10 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Networks for Perception, Volume 2: Computation, Learning, and Architectures explores the computational and adaptation problems related to the use of neuronal systems, and the corresponding hardware architectures capable of implementing neural networks for perception and of coping with the complexity inherent in massively distributed computation. This book addresses both theoretical and practical issues related to the feasibility of both explaining human perception and implementing machine perception in terms of neural network models. The text is organized into two sections. The first section, computation and learning, discusses topics on learning visual behaviors, some of the elementary theory of the basic backpropagation neural network architecture, and computation and learning in the context of neural network capacity. The second section is on hardware architecture. The chapters included in this part of the book describe the architectures and possible applications of recent neurocomputing models. The Cohen-Grossberg model of associative memory, hybrid optical/digital architectures for neorocomputing, and electronic circuits for adaptive synapses are some of the subjects elucidated. Neuroscientists, computer scientists, engineers, and researchers in artificial intelligence will find the book useful.
Book Synopsis Multidimensional Data Visualization by : Gintautas Dzemyda
Download or read book Multidimensional Data Visualization written by Gintautas Dzemyda and published by Springer Science & Business Media. This book was released on 2012-11-08 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights recent developments in multidimensional data visualization, presenting both new methods and modifications on classic techniques. Throughout the book, various applications of multidimensional data visualization are presented including its uses in social sciences (economy, education, politics, psychology), environmetrics, and medicine (ophthalmology, sport medicine, pharmacology, sleep medicine). The book provides recent research results in optimization-based visualization. Evolutionary algorithms and a two-level optimization method, based on combinatorial optimization and quadratic programming, are analyzed in detail. The performance of these algorithms and the development of parallel versions are discussed. The utilization of new visualization techniques to improve the capabilies of artificial neural networks (self-organizing maps, feed-forward networks) is also discussed. The book includes over 100 detailed images presenting examples of the many different visualization techniques that the book presents. This book is intended for scientists and researchers in any field of study where complex and multidimensional data must be represented visually.
Book Synopsis Analysis of Complex Data Sets Using Multilayer Networks by : Abhishek Santra
Download or read book Analysis of Complex Data Sets Using Multilayer Networks written by Abhishek Santra and published by . This book was released on 2020 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are on the cusp of analyzing a variety of data being collected in every walk of life - social, biological, health-care, corporate, climate, to name a few. The datasets are becoming diverse and complex in addition to increased size. Some of the complexity comes from interacting entities that arise in diverse disciplines, such as epidemiology [1], marketing strategy [2], social sciences [3], cybersecurity [4] and drug design [5]. Data sets becoming diverse and complex entails search for appropriate models and concomitant analytical techniques that are also efficient. Our ability to analyze large, complex, and disparate data for a broad set of analysis objectives differentiates big data analytics from mining which is narrow in scope both from data and analysis perspective. For big data analytics, flexibility of analysis (different from scalability)is important. Efficiency is important due to large number of analysis needs. Elegantly modeling and efficiently analyzing these complex datasets to obtain actionable knowledge presents several challenges. Traditional approaches, such as using single graph (or a single layer network or monoplex) may not be sufficient or appropriate for modeling and computation flexibility. Recently, multilayer networks have been proposed as an alternative for modeling such data elegantly. In this thesis, we first discuss different types of multilayer networks - homogeneous, heterogeneous and hybrid - from a modeling perspective. The benefits of this modeling, in terms of ease, understanding, and usage, are highlighted. Although big data analysis has warranted many new data models, not much attention has been paid to their modeling from requirements. Going straight from application requirements to data model and analysis, especially for complex data sets, is likely to be difficult, error prone, and not extensible to say the least. Hence for data models used in big data analysis, such as Multilayer Networks, there is a need to algorithmically transform the requirements using a systematic modeling approach, such as EER (Enhanced Entity Relationship). Here, we start with application requirements of complex data sets including analysis objectives and show how the EER approach can be leveraged for modeling given data to generate the MLN model and appropriate analysis expressions on them. However, this model brings with it a new set of challenges - both algorithmically and efficiency-wise - for its analysis. Since there are not many algorithms available in the literature for the analysis of MLN as a whole, applying currently available techniques to a transformed version of MLN leads to loss of information in terms of structure and semantics. Our proposed approach is to develop an analysis framework without transforming the MLN model so structure and semantics can be easily preserved. The general framework proposed and developed in this thesis is termed network decoupling. This framework is intended to be beneficial to all aggregate computations although this thesis focuses on two of them. The essence of this approach is to analyze each network layer individually and then use a composition function for aggregating individual layer results. This thesis demonstrates the network decoupling approach and its merits for widely-used graph aggregation analysis, such as community and centrality. For both community and centrality detection of MLN using Boolean operators, efficient composition functions and algorithms have been developed and validated for Homogeneous Multilayer Networks. To demonstrate its effectiveness, this thesis has proposed a new community definition of heterogeneous MLNs using the same framework. This not only uses the decoupling approach based on bipartite graph matching, but also preserves structure and semantics. Structure and semantics preservation for MLNs (both homogeneous and heterogeneous) is crucial for drill down analysis to clearly understand and interpret results. Our definition supports a family of community detection algorithms for heterogeneous MLNs which is very useful for matching analysis objectives. Further, for a broader analysis, we introduce several weight metrics for bringing in individual layer community characteristics on the MLN community. Essentially, this results in an extensible family of community computations. Finally, the framework and the algorithms proposed have been applied to real world (Internet Movie Database - IMDb, Database Bibliography - DBLP, UK Accidents, US Airlines, Facebook) and synthetic data sets in order to validate the approach, flexibility afforded, accuracy limits, and efficiency aspects. Meticulous drill down analysis on the final results has been carried out to come up with few surprising analysis results that predicted future potential events that we could verify by independently available ground truth. Based on this work, a dashboard for visualizing MLN analysis is underway.
Book Synopsis Computer Vision -- ECCV 2014 by : David Fleet
Download or read book Computer Vision -- ECCV 2014 written by David Fleet and published by Springer. This book was released on 2014-09-22 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.
Book Synopsis Multilayer Networks by : Ginestra Bianconi
Download or read book Multilayer Networks written by Ginestra Bianconi and published by Oxford University Press. This book was released on 2018-06-07 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilayer networks is a rising topic in Network Science which characterizes the structure and the function of complex systems formed by several interacting networks. Multilayer networks research has been propelled forward by the wide realm of applications in social, biological and infrastructure networks and the large availability of network data, as well as by the significance of recent results, which have produced important advances in this rapidly growing field. This book presents a comprehensive account of this emerging field. It provides a theoretical introduction to the main results of multilayer network science.
Book Synopsis Multiscale Visual Analysis of Dynamic Networks by : Eren Cakmak
Download or read book Multiscale Visual Analysis of Dynamic Networks written by Eren Cakmak and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dynamical Systems on Networks by : Mason Porter
Download or read book Dynamical Systems on Networks written by Mason Porter and published by Springer. This book was released on 2016-03-31 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a tutorial for the study of dynamical systems on networks. It discusses both methodology and models, including spreading models for social and biological contagions. The authors focus especially on “simple” situations that are analytically tractable, because they are insightful and provide useful springboards for the study of more complicated scenarios. This tutorial, which also includes key pointers to the literature, should be helpful for junior and senior undergraduate students, graduate students, and researchers from mathematics, physics, and engineering who seek to study dynamical systems on networks but who may not have prior experience with graph theory or networks. Mason A. Porter is Professor of Nonlinear and Complex Systems at the Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, UK. He is also a member of the CABDyN Complexity Centre and a Tutorial Fellow of Somerville College. James P. Gleeson is Professor of Industrial and Applied Mathematics, and co-Director of MACSI, at the University of Limerick, Ireland.
Book Synopsis Complex Networks and Their Applications VII by : Luca Maria Aiello
Download or read book Complex Networks and Their Applications VII written by Luca Maria Aiello and published by Springer. This book was released on 2018-12-01 with total page 906 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory, together with a wealth of applications. It presents the peer-reviewed proceedings of the VII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2018), which was held in Cambridge on December 11–13, 2018. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure and network dynamics; diffusion, epidemics and spreading processes; and resilience and control; as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks.
Book Synopsis Deep Learning for Robot Perception and Cognition by : Alexandros Iosifidis
Download or read book Deep Learning for Robot Perception and Cognition written by Alexandros Iosifidis and published by Academic Press. This book was released on 2022-02-04 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. Presents deep learning principles and methodologies Explains the principles of applying end-to-end learning in robotics applications Presents how to design and train deep learning models Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more Uses robotic simulation environments for training deep learning models Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis
