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Author : Arun S. Maiya
Publisher :
ISBN 13 :
Total Pages : 444 pages
Book Rating : 4.:/5 (773 download)
Download or read book Sampling and Inference in Complex Networks written by Arun S. Maiya and published by . This book was released on 2011 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Scott T. Weidman
Publisher : National Academies Press
ISBN 13 : 0309101050
Total Pages : 470 pages
Book Rating : 4.3/5 (91 download)
Download or read book Proceedings of a Workshop on Statistics on Networks written by Scott T. Weidman and published by National Academies Press. This book was released on 2007-10-30 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: A large number of biological, physical, and social systems contain complex networks. Knowledge about how these networks operate is critical for advancing a more general understanding of network behavior. To this end, each of these disciplines has created different kinds of statistical theory for inference on network data. To help stimulate further progress in the field of statistical inference on network data, the NRC sponsored a workshop that brought together researchers who are dealing with network data in different contexts. This book - which is available on CD only - contains the text of the 18 workshop presentations. The presentations focused on five major areas of research: network models, dynamic networks, data and measurement on networks, robustness and fragility of networks, and visualization and scalability of networks.
Author : Eric D. Kolaczyk
Publisher : Springer Science & Business Media
ISBN 13 : 0387881468
Total Pages : 397 pages
Book Rating : 4.3/5 (878 download)
Download or read book Statistical Analysis of Network Data written by Eric D. Kolaczyk and published by Springer Science & Business Media. This book was released on 2009-04-20 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.
Author : Fakhteh Ghanbarnejad
Publisher : Springer
ISBN 13 : 3030146839
Total Pages : 244 pages
Book Rating : 4.0/5 (31 download)
Download or read book Dynamics On and Of Complex Networks III written by Fakhteh Ghanbarnejad and published by Springer. This book was released on 2019-05-13 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book bridges the gap between advances in the communities of computer science and physics--namely machine learning and statistical physics. It contains diverse but relevant topics in statistical physics, complex systems, network theory, and machine learning. Examples of such topics are: predicting missing links, higher-order generative modeling of networks, inferring network structure by tracking the evolution and dynamics of digital traces, recommender systems, and diffusion processes. The book contains extended versions of high-quality submissions received at the workshop, Dynamics On and Of Complex Networks (doocn.org), together with new invited contributions. The chapters will benefit a diverse community of researchers. The book is suitable for graduate students, postdoctoral researchers and professors of various disciplines including sociology, physics, mathematics, and computer science.
Author : Juliane Manitz
Publisher :
ISBN 13 : 9783843916684
Total Pages : 201 pages
Book Rating : 4.9/5 (166 download)
Download or read book Statistical Inference for Propagation Processes on Complex Networks written by Juliane Manitz and published by . This book was released on 2014 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Marco Scutari
Publisher : CRC Press
ISBN 13 : 1000410382
Total Pages : 275 pages
Book Rating : 4.0/5 (4 download)
Download or read book Bayesian Networks written by Marco Scutari and published by CRC Press. This book was released on 2021-07-28 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the material step-by-step starting from meaningful examples Steps detailed with R code in the spirit of reproducible research Real world data analyses from a Science paper reproduced and explained in detail Examples span a variety of fields across social and life sciences Overview of available software in and outside R
Author : Eric D. Kolaczyk
Publisher : Springer
ISBN 13 : 1493909835
Total Pages : 214 pages
Book Rating : 4.4/5 (939 download)
Download or read book Statistical Analysis of Network Data with R written by Eric D. Kolaczyk and published by Springer. This book was released on 2014-05-22 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).
Author : Rosa M. Benito
Publisher : Springer Nature
ISBN 13 : 3030653471
Total Pages : 702 pages
Book Rating : 4.0/5 (36 download)
Download or read book Complex Networks & Their Applications IX written by Rosa M. Benito and published by Springer Nature. This book was released on 2020-12-19 with total page 702 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 and a multitude of applications. It presents the peer-reviewed proceedings of the IX International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2020). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; 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.
Author : Hocine Cherifi
Publisher : Springer Nature
ISBN 13 : 3031211316
Total Pages : 674 pages
Book Rating : 4.0/5 (312 download)
Download or read book Complex Networks and Their Applications XI written by Hocine Cherifi and published by Springer Nature. This book was released on 2023-01-25 with total page 674 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 and a multitude of applications. It presents the peer-reviewed proceedings of the XI International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2022). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; 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.
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 : Huy Nguyen
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (859 download)
Download or read book Interactions on Complex Networks written by Huy Nguyen and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex networks are ubiquitous -from social and information systems to biological and technological systems. Such networks are platforms for interaction, communication, and collaboration among distributed entities. Studying and analyzing observable network interactions are therefore crucial to understand the hidden complex network properties. However, with pervasive adoption of the Internet and technology advancements, networks under study today are not only substantially larger than those in the past, but are often highly distributed over large geographical areas. Along with this massive scale, the volume of interaction data also presents a serious challenge to network analysis and data mining techniques. This dissertation focuses on developing inference solutions to complex networks from different domains and applying them in solving practical problems in information and social sciences. In the first part of the dissertation, we propose Binary Independent Component Analysis with OR Mixtures (bICA), an inference algorithm specialized for communication networks that can be formulated as a bipartite graph. Then we apply bICA and its variants to solve a wide range of networking problems, ranging from optimal monitoring and primary user separation in wireless networks to multicast network tree topology inference. Evaluation results show that the methodology is not only more accurate than previous approaches, but also more robust against measurement noise. In the second part, we extend our study to the online social networking domain, where the networks are both massive and dynamic. We conduct an extensive analysis on Twitter and associated influence ranking services. Several interesting discoveries have been made, which challenge some of the basic assumptions that many researchers made in the past. We also investigate the problem of finding the set of most influential entities on social networks given a limited budget. Experiments conducted on both large-scale social networks and synthetically generated networks demonstrate the effectiveness of the proposed solution.
Author : Harry Crane
Publisher : CRC Press
ISBN 13 : 1351807331
Total Pages : 236 pages
Book Rating : 4.3/5 (518 download)
Download or read book Probabilistic Foundations of Statistical Network Analysis written by Harry Crane and published by CRC Press. This book was released on 2018-04-17 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic network models, network sampling, and network statistics such as sparsity and power law, all of which play a central role in contemporary data science and machine learning applications. The book rewards readers with a clear and intuitive understanding of the subtle interplay between basic principles of statistical inference, empirical properties of network data, and technical concepts from probability theory. Its mathematically rigorous, yet non-technical, exposition makes the book accessible to professional data scientists, statisticians, and computer scientists as well as practitioners and researchers in substantive fields. Newcomers and non-quantitative researchers will find its conceptual approach invaluable for developing intuition about technical ideas from statistics and probability, while experts and graduate students will find the book a handy reference for a wide range of new topics, including edge exchangeability, relative exchangeability, graphon and graphex models, and graph-valued Levy process and rewiring models for dynamic networks. The author’s incisive commentary supplements these core concepts, challenging the reader to push beyond the current limitations of this emerging discipline. With an approachable exposition and more than 50 open research problems and exercises with solutions, this book is ideal for advanced undergraduate and graduate students interested in modern network analysis, data science, machine learning, and statistics. Harry Crane is Associate Professor and Co-Director of the Graduate Program in Statistics and Biostatistics and an Associate Member of the Graduate Faculty in Philosophy at Rutgers University. Professor Crane’s research interests cover a range of mathematical and applied topics in network science, probability theory, statistical inference, and mathematical logic. In addition to his technical work on edge and relational exchangeability, relative exchangeability, and graph-valued Markov processes, Prof. Crane’s methods have been applied to domain-specific cybersecurity and counterterrorism problems at the Foreign Policy Research Institute and RAND’s Project AIR FORCE.
Author : Vasileios Karyotis
Publisher : Morgan Kaufmann
ISBN 13 : 0128027169
Total Pages : 326 pages
Book Rating : 4.1/5 (28 download)
Download or read book Malware Diffusion Models for Modern Complex Networks written by Vasileios Karyotis and published by Morgan Kaufmann. This book was released on 2016-02-02 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Malware Diffusion Models for Wireless Complex Networks: Theory and Applications provides a timely update on malicious software (malware), a serious concern for all types of network users, from laymen to experienced administrators. As the proliferation of portable devices, namely smartphones and tablets, and their increased capabilities, has propelled the intensity of malware spreading and increased its consequences in social life and the global economy, this book provides the theoretical aspect of malware dissemination, also presenting modeling approaches that describe the behavior and dynamics of malware diffusion in various types of wireless complex networks. Sections include a systematic introduction to malware diffusion processes in computer and communications networks, an analysis of the latest state-of-the-art malware diffusion modeling frameworks, such as queuing-based techniques, calculus of variations based techniques, and game theory based techniques, also demonstrating how the methodologies can be used for modeling in more general applications and practical scenarios. Presents a timely update on malicious software (malware), a serious concern for all types of network users, from laymen to experienced administrators Systematically introduces malware diffusion processes, providing the relevant mathematical background Discusses malware modeling frameworks and how to apply them to complex wireless networks Provides guidelines and directions for extending the corresponding theories in other application domains, demonstrating such possibility by using application models in information dissemination scenarios
Author : Hocine Cherifi
Publisher : Springer Nature
ISBN 13 : 3031535030
Total Pages : 490 pages
Book Rating : 4.0/5 (315 download)
Download or read book Complex Networks & Their Applications XII written by Hocine Cherifi and published by Springer Nature. This book was released on with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : European Coordinating Committee for Artificial Intelligence
Publisher : IOS Press
ISBN 13 : 1586038915
Total Pages : 972 pages
Book Rating : 4.5/5 (86 download)
Download or read book ECAI 2008 written by European Coordinating Committee for Artificial Intelligence and published by IOS Press. This book was released on 2008 with total page 972 pages. Available in PDF, EPUB and Kindle. Book excerpt: Includes subconference "Prestigious Applications of Intelligent Systems (PAIS 2008)."
Author : Hocine Cherifi
Publisher : Springer Nature
ISBN 13 : 3030366871
Total Pages : 992 pages
Book Rating : 4.0/5 (33 download)
Download or read book Complex Networks and Their Applications VIII written by Hocine Cherifi and published by Springer Nature. This book was released on 2019-11-25 with total page 992 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 and a multitude of applications. It presents the peer-reviewed proceedings of the Eighth International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2019), which took place in Lisbon, Portugal, on December 10–12, 2019. 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; 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.
Author : Claus Skaanning Jensen
Publisher :
ISBN 13 :
Total Pages : 220 pages
Book Rating : 4.:/5 (39 download)
Download or read book Blocking Gibbs Sampling for Inference in Large and Complex Bayesian Networks with Applications in Genetics written by Claus Skaanning Jensen and published by . This book was released on 1997 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:
