Generating Random Networks and Graphs

Author: Alessia Annibale,Ton Coolen,Ekaterina Roberts
Publisher: Oxford University Press
ISBN: 0198709897
Page: 310
View: 4928
Generating random networks efficiently and accurately is an important challenge for practical applications, and an interesting question for theoretical study. This book presents and discusses common methods of generating random graphs. It begins with approaches such as Exponential Random Graph Models, where the targeted probability of each network appearing in the ensemble is specified. This section also includes degree-preserving randomisation algorithms, where the aim is to generate networks with the correct number of links at each node, and care must be taken to avoid introducing a bias. Separately, it looks at growth style algorithms (e.g. preferential attachment) which aim to model a real process and then to analyse the resulting ensemble of graphs. It also covers how to generate special types of graphs including modular graphs, graphs with community structure and temporal graphs. The book is aimed at the graduate student or advanced undergraduate. It includes many worked examples and open questions making it suitable for use in teaching. Explicit pseudocode algorithms are included throughout the book to make the ideas straightforward to apply. With larger and larger datasets, it is crucial to have practical and well-understood tools. Being able to test a hypothesis against a properly specified control case is at the heart of the 'scientific method'. Hence, knowledge on how to generate controlled and unbiased random graph ensembles is vital for anybody wishing to apply network science in their research.

The Structure and Dynamics of Networks:

Author: Mark Newman,Albert-László Barabási,Duncan J. Watts
Publisher: Princeton University Press
ISBN: 0691113572
Category: Mathematics
Page: 582
View: 2872
From the Internet to networks of friendship, disease transmission, and even terrorism, the concept--and the reality--of networks has come to pervade modern society. But what exactly is a network? What different types of networks are there? Why are they interesting, and what can they tell us? In recent years, scientists from a range of fields--including mathematics, physics, computer science, sociology, and biology--have been pursuing these questions and building a new "science of networks." This book brings together for the first time a set of seminal articles representing research from across these disciplines. It is an ideal sourcebook for the key research in this fast-growing field. The book is organized into four sections, each preceded by an editors' introduction summarizing its contents and general theme. The first section sets the stage by discussing some of the historical antecedents of contemporary research in the area. From there the book moves to the empirical side of the science of networks before turning to the foundational modeling ideas that have been the focus of much subsequent activity. The book closes by taking the reader to the cutting edge of network science--the relationship between network structure and system dynamics. From network robustness to the spread of disease, this section offers a potpourri of topics on this rapidly expanding frontier of the new science.

Information Networking. Networking Technologies for Broadband and Mobile Networks

International Conference ICOIN 2004, Busan, Korea, February 18-20, 2004, Revised Selected Papers
Author: Hyun-Kook Kahng
Publisher: Springer
ISBN: 3540259783
Category: Computers
Page: 1048
View: 1212
This book constitutes the thoroughly refereed post proceedings of the International Conference on Information Networking, ICOIN 2004, held in Busan, Korea, in February 2004. The 104 revised full papers presented were carefully selected during two rounds of reviewing and revision. The papers are organized in topical sections on mobile Internet and ubiquitous computing; QoS, measurement and performance analysis; high-speed network technologies; next generation Internet architecture; security; and Internet applications.

Counterterrorism and Open Source Intelligence

Author: Uffe Wiil
Publisher: Springer Science & Business Media
ISBN: 9783709103883
Category: Computers
Page: 458
View: 495
Since the 9/11 terrorist attacks in the United States, serious concerns were raised on domestic and international security issues. Consequently, there has been considerable interest recently in technological strategies and resources to counter acts of terrorism. In this context, this book provides a state-of-the-art survey of the most recent advances in the field of counterterrorism and open source intelligence, demonstrating how various existing as well as novel tools and techniques can be applied in combating covert terrorist networks. A particular focus will be on future challenges of open source intelligence and perspectives on how to effectively operate in order to prevent terrorist activities.

Web and Network Data Science

Modeling Techniques in Predictive Analytics
Author: Thomas W. Miller
Publisher: FT Press
ISBN: 0133887642
Category: Computers
Page: 384
View: 8954
Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.

Computational Science - ICCS 2003

International Conference, Melbourne, Australia and St. Petersburg, Russia, June 2-4, 2003. Proceedings
Author: Peter M.A. Sloot,David Abramson,Alexander V. Bogdanov,Jack J. Dongarra,Albert Y. Zomaya,Yuriy E. Gorbachev
Publisher: Springer Science & Business Media
ISBN: 3540401954
Category: Computers
Page: 1131
View: 7008
The four-volume set LNCS 2657, LNCS 2658, LNCS 2659, and LNCS 2660 constitutes the refereed proceedings of the Third International Conference on Computational Science, ICCS 2003, held concurrently in Melbourne, Australia and in St. Petersburg, Russia in June 2003. The four volumes present more than 460 reviewed contributed and invited papers and span the whole range of computational science, from foundational issues in computer science and algorithmic mathematics to advanced applications in virtually all application fields making use of computational techniques. These proceedings give a unique account of recent results in the field.

Exploratory Social Network Analysis with Pajek

Author: Wouter De Nooy,Andrej Mrvar,Vladimir Batagelj
Publisher: Cambridge University Press
ISBN: 1108474144
Category: Language Arts & Disciplines
Page: 450
View: 8154
The textbook on analysis and visualization of social networks that integrates theory, applications, and professional software for performing network analysis. Pajek software and datasets for all examples are freely available, so the reader can learn network analysis by doing it. Each chapter offers case studies for practicing network analysis.

Dynamics On and Of Complex Networks

Applications to Biology, Computer Science, and the Social Sciences
Author: Niloy Ganguly,Andreas Deutsch,Animesh Mukherjee
Publisher: Springer Science & Business Media
ISBN: 0817647503
Category: Computers
Page: 305
View: 4266
This self-contained book systematically explores the statistical dynamics on and of complex networks having relevance across a large number of scientific disciplines. The theories related to complex networks are increasingly being used by researchers for their usefulness in harnessing the most difficult problems of a particular discipline. The book is a collection of surveys and cutting-edge research contributions exploring the interdisciplinary relationship of dynamics on and of complex networks. Topics covered include complex networks found in nature—genetic pathways, ecological networks, linguistic systems, and social systems—as well as man-made systems such as the World Wide Web and peer-to-peer networks. The contributed chapters in this volume are intended to promote cross-fertilization in several research areas, and will be valuable to newcomers in the field, experienced researchers, practitioners, and graduate students interested in systems exhibiting an underlying complex network structure in disciplines such as computer science, biology, statistical physics, nonlinear dynamics, linguistics, and the social sciences.

Graphs, Networks and Algorithms

Author: Dieter Jungnickel
Publisher: Springer Science & Business Media
ISBN: 3642322786
Category: Mathematics
Page: 676
View: 3056
From the reviews of the previous editions ".... The book is a first class textbook and seems to be indispensable for everybody who has to teach combinatorial optimization. It is very helpful for students, teachers, and researchers in this area. The author finds a striking synthesis of nice and interesting mathematical results and practical applications. ... the author pays much attention to the inclusion of well-chosen exercises. The reader does not remain helpless; solutions or at least hints are given in the appendix. Except for some small basic mathematical and algorithmic knowledge the book is self-contained. ..." K.Engel, Mathematical Reviews 2002 The substantial development effort of this text, involving multiple editions and trailing in the context of various workshops, university courses and seminar series, clearly shows through in this new edition with its clear writing, good organisation, comprehensive coverage of essential theory, and well-chosen applications. The proofs of important results and the representation of key algorithms in a Pascal-like notation allow this book to be used in a high-level undergraduate or low-level graduate course on graph theory, combinatorial optimization or computer science algorithms. The well-worked solutions to exercises are a real bonus for self study by students. The book is highly recommended. P .B. Gibbons, Zentralblatt für Mathematik 2005 Once again, the new edition has been thoroughly revised. In particular, some further material has been added: more on NP-completeness (especially on dominating sets), a section on the Gallai-Edmonds structure theory for matchings, and about a dozen additional exercises – as always, with solutions. Moreover, the section on the 1-factor theorem has been completely rewritten: it now presents a short direct proof for the more general Berge-Tutte formula. Several recent research developments are discussed and quite a few references have been added.

Models and Algorithms for Biomolecules and Molecular Networks

Author: Bhaskar DasGupta,Jie Liang
Publisher: John Wiley & Sons
ISBN: 1119162270
Category: Science
Page: 264
View: 4269
By providing expositions to modeling principles, theories, computational solutions, and open problems, this reference presents a full scope on relevant biological phenomena, modeling frameworks, technical challenges, and algorithms. Up-to-date developments of structures of biomolecules, systems biology, advanced models, and algorithms Sampling techniques for estimating evolutionary rates and generating molecular structures Accurate computation of probability landscape of stochastic networks, solving discrete chemical master equations End-of-chapter exercises

An Introduction to Exponential Random Graph Modeling

Author: Jenine K. Harris
Publisher: SAGE Publications
ISBN: 148332205X
Category: Social Science
Page: 136
View: 7312
This volume introduces the basic concepts of Exponential Random Graph Modeling (ERGM), gives examples of why it is used, and shows the reader how to conduct basic ERGM analyses in their own research. ERGM is a statistical approach to modeling social network structure that goes beyond the descriptive methods conventionally used in social network analysis. Although it was developed to handle the inherent non-independence of network data, the results of ERGM are interpreted in similar ways to logistic regression, making this a very useful method for examining social systems. Recent advances in statistical software have helped make ERGM accessible to social scientists, but a concise guide to using ERGM has been lacking. An Introduction to Exponential Random Graph Modeling, by Jenine K. Harris, fills that gap, by using examples from public health, and walking the reader through the process of ERGM model-building using R statistical software and the statnet package.

Networking ...

Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications : ... International IFIP-TC6 Networking Conference ... Proceedings
Author: Nikolas Mitrou
Publisher: Springer
Category: Computer networks
Page: N.A
View: 7262

A Graph-Theoretic Approach to Enterprise Network Dynamics

Author: Horst Bunke,Peter J. Dickinson,Miro Kraetzl,Walter D. Wallis
Publisher: Springer Science & Business Media
ISBN: 9780817645199
Category: Computers
Page: 226
View: 5748
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.

Animal Social Networks

Author: Jens Krause,Richard James,Daniel Franks,Darren Croft
Publisher: OUP Oxford
ISBN: 019166829X
Category: Science
Page: 288
View: 4696
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.

Trends and Research in the Decision Sciences

Best Papers from the 2014 Annual Conference
Author: Decision Sciences Institute,Merrill Warkentin
Publisher: FT Press
ISBN: 0133925536
Category: Computers
Page: 400
View: 9985
Decision science offers powerful insights and techniques that help people make better decisions to improve business and society. This new volume brings together the peer-reviewed papers that have been chosen as the "best of the best" by the field's leading organization, the Decision Sciences Institute. These papers, authored by respected decision science researchers and academics from around the world, will be presented at DSI's 45th Annual Meeting in Tampa, Florida in November 2014. The first book of papers ever assembled by DSI, this volume describes recent methods and approaches in the decision sciences, with a special focus on how accelerating technological innovation is driving change in the ways organizations and individuals make decisions. These papers offer actionable insights for decision-makers of all kinds, in business, public policy, non-profit organizations, and beyond. They also point to new research directions for academic researchers in decision science worldwide.

Fundamentals of Complex Networks

Models, Structures and Dynamics
Author: Guanrong Chen,Xiaofan Wang,Xiang Li
Publisher: John Wiley & Sons
ISBN: 1118718143
Category: Computers
Page: 392
View: 2965
Complex networks such as the Internet, WWW, transportation networks, power grids, biological neural networks, and scientific cooperation networks of all kinds provide challenges for future technological development. • The first systematic presentation of dynamical evolving networks, with many up-to-date applications and homework projects to enhance study • The authors are all very active and well-known in the rapidly evolving field of complex networks • Complex networks are becoming an increasingly important area of research • Presented in a logical, constructive style, from basic through to complex, examining algorithms, through to construct networks and research challenges of the future

Random Networks for Communication

From Statistical Physics to Information Systems
Author: Massimo Franceschetti,Ronald Meester
Publisher: Cambridge University Press
ISBN: 1139467697
Category: Mathematics
Page: N.A
View: 7652
When is a random network (almost) connected? How much information can it carry? How can you find a particular destination within the network? And how do you approach these questions - and others - when the network is random? The analysis of communication networks requires a fascinating synthesis of random graph theory, stochastic geometry and percolation theory to provide models for both structure and information flow. This book is the first comprehensive introduction for graduate students and scientists to techniques and problems in the field of spatial random networks. The selection of material is driven by applications arising in engineering, and the treatment is both readable and mathematically rigorous. Though mainly concerned with information-flow-related questions motivated by wireless data networks, the models developed are also of interest in a broader context, ranging from engineering to social networks, biology, and physics.

Random Walks and Diffusions on Graphs and Databases

An Introduction
Author: Philipp Blanchard,Dimitri Volchenkov
Publisher: Springer Science & Business Media
ISBN: 9783642195921
Category: Science
Page: 262
View: 6946
Most networks and databases that humans have to deal with contain large, albeit finite number of units. Their structure, for maintaining functional consistency of the components, is essentially not random and calls for a precise quantitative description of relations between nodes (or data units) and all network components. This book is an introduction, for both graduate students and newcomers to the field, to the theory of graphs and random walks on such graphs. The methods based on random walks and diffusions for exploring the structure of finite connected graphs and databases are reviewed (Markov chain analysis). This provides the necessary basis for consistently discussing a number of applications such diverse as electric resistance networks, estimation of land prices, urban planning, linguistic databases, music, and gene expression regulatory networks.

Algorithms and Models for the Web-Graph

Third International Workshop, WAW 2004, Rome, Italy, October 16, 2004. Proceedings
Author: Workshop on Algorithms and Models for the Web-Graph
Publisher: Springer Science & Business Media
ISBN: 9783540234272
Category: Computers
Page: 187
View: 927
This book constitutes the refereed proceedings of the Third International Workshop on Algorithms and Models for the Web-Graph, WAW 2004, held in Rome, Italy in October 2004. The 14 revised full papers presented together with an invited paper were carefully reviewed and selected from 31 submissions. The papers address a variety of topics related to the study of the Web-graph including random graphs, local network flow, network models, traffic driven Web-graph modeling, embedded communities, Web data mining, personalization, page rank computation, hierarchical information networks, Web crawling, community detection, and network communities.

Statistical and Machine Learning Approaches for Network Analysis

Author: Matthias Dehmer,Subhash C. Basak
Publisher: John Wiley & Sons
ISBN: 111834698X
Category: Mathematics
Page: 344
View: 1612
Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networks An introduction to complex networks—measures, statistical properties, and models Modeling for evolving biological networks The structure of an evolving random bipartite graph Density-based enumeration in structured data Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.