Algorithmics Of Large And Complex Networks

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Algorithmics of Large and Complex Networks

Jürgen Lerner,Dorothea Wagner,Katharina Zweig
Algorithmics of Large and Complex Networks Book PDF

Author : Jürgen Lerner,Dorothea Wagner,Katharina Zweig
Publisher : Springer
Page : 401 pages
File Size : 50,7 Mb
Release : 2009-06-29
Category : Computers
ISBN : 9783642020940

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Algorithmics of Large and Complex Networks by Jürgen Lerner,Dorothea Wagner,Katharina Zweig Pdf

Networks play a central role in today’s society, since many sectors employing information technology, such as communication, mobility, and transport - even social interactions and political activities - are based on and rely on networks. In these times of globalization and the current global financial crisis with its complex and nearly incomprehensible entanglements of various structures and its huge effect on seemingly unrelated institutions and organizations, the need to understand large networks, their complex structures, and the processes governing them is becoming more and more important. This state-of-the-art survey reports on the progress made in selected areas of this important and growing field, thus helping to analyze existing large and complex networks and to design new and more efficient algorithms for solving various problems on these networks since many of them have become so large and complex that classical algorithms are not sufficient anymore. This volume emerged from a research program funded by the German Research Foundation (DFG) consisting of projects focusing on the design of new discrete algorithms for large and complex networks. The 18 papers included in the volume present the results of projects realized within the program and survey related work. They have been grouped into four parts: network algorithms, traffic networks, communication networks, and network analysis and simulation.

Algorithmics of Large and Complex Networks

Jürgen Lerner,Dorothea Wagner,Katharina Zweig
Algorithmics of Large and Complex Networks Book PDF

Author : Jürgen Lerner,Dorothea Wagner,Katharina Zweig
Publisher : Springer Science & Business Media
Page : 411 pages
File Size : 41,9 Mb
Release : 2009-07-02
Category : Computers
ISBN : 9783642020933

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Algorithmics of Large and Complex Networks by Jürgen Lerner,Dorothea Wagner,Katharina Zweig Pdf

A state-of-the-art survey that reports on the progress made in selected areas of this important and growing field, aiding the analysis of existing networks and the design of new and more efficient algorithms for solving various problems on these networks.

Big Data of Complex Networks

Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl,Andreas Holzinger
Big Data of Complex Networks Book PDF

Author : Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl,Andreas Holzinger
Publisher : CRC Press
Page : 332 pages
File Size : 42,8 Mb
Release : 2016-08-19
Category : Computers
ISBN : 9781498723626

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Big Data of Complex Networks by Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl,Andreas Holzinger Pdf

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.

Complex Networks

Kayhan Erciyes
Complex Networks Book PDF

Author : Kayhan Erciyes
Publisher : CRC Press
Page : 318 pages
File Size : 40,7 Mb
Release : 2014-09-06
Category : Computers
ISBN : 9781466571679

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Complex Networks by Kayhan Erciyes Pdf

Network science is a rapidly emerging field of study that encompasses mathematics, computer science, physics, and engineering. A key issue in the study of complex networks is to understand the collective behavior of the various elements of these networks.Although the results from graph theory have proven to be powerful in investigating the structur

Mining Complex Networks

Bogumil Kaminski,Pawel Prałat,Francois Theberge
Mining Complex Networks Book PDF

Author : Bogumil Kaminski,Pawel Prałat,Francois Theberge
Publisher : CRC Press
Page : 278 pages
File Size : 49,8 Mb
Release : 2021-12-15
Category : Mathematics
ISBN : 9781000515855

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Mining Complex Networks by Bogumil Kaminski,Pawel Prałat,Francois Theberge Pdf

This book concentrates on mining networks, a subfield within data science. Data science uses scientific and computational tools to extract valuable knowledge from large data sets. Once data is processed and cleaned, it is analyzed and presented to support decision-making processes. Data science and machine learning tools have become widely used in companies of all sizes. Networks are often large-scale, decentralized, and evolve dynamically over time. Mining complex networks aim to understand the principles governing the organization and the behavior of such networks is crucial for a broad range of fields of study. Here are a few selected typical applications of mining networks: Community detection (which users on some social media platforms are close friends). Link prediction (who is likely to connect to whom on such platforms). Node attribute prediction (what advertisement should be shown to a given user of a particular platform to match their interests). Influential node detection (which social media users would be the best ambassadors of a specific product). This textbook is suitable for an upper-year undergraduate course or a graduate course in programs such as data science, mathematics, computer science, business, engineering, physics, statistics, and social science. This book can be successfully used by all enthusiasts of data science at various levels of sophistication to expand their knowledge or consider changing their career path. Jupiter notebooks (in Python and Julia) accompany the book and can be accessed on https://www.ryerson.ca/mining-complex-networks/. These not only contain all the experiments presented in the book, but also include additional material. Bogumił Kamiński is the Chairman of the Scientific Council for the Discipline of Economics and Finance at SGH Warsaw School of Economics. He is also an Adjunct Professor at the Data Science Laboratory at Ryerson University. Bogumił is an expert in applications of mathematical modeling to solving complex real-life problems. He is also a substantial open-source contributor to the development of the Julia language and its package ecosystem. Paweł Prałat is a Professor of Mathematics in Ryerson University, whose main research interests are in random graph theory, especially in modeling and mining complex networks. He is the Director of Fields-CQAM Lab on Computational Methods in Industrial Mathematics in The Fields Institute for Research in Mathematical Sciences and has pursued collaborations with various industry partners as well as the Government of Canada. He has written over 170 papers and three books with 130 plus collaborators. François Théberge holds a B.Sc. degree in applied mathematics from the University of Ottawa, a M.Sc. in telecommunications from INRS and a PhD in electrical engineering from McGill University. He has been employed by the Government of Canada since 1996 where he was involved in the creation of the data science team as well as the research group now known as the Tutte Institute for Mathematics and Computing. He also holds an adjunct professorial position in the Department of Mathematics and Statistics at the University of Ottawa. His current interests include relational-data mining and deep learning.

Methods and algorithms for control input placement in complex networks

Gustav Lindmark
Methods and algorithms for control input placement in complex networks Book PDF

Author : Gustav Lindmark
Publisher : Linköping University Electronic Press
Page : 36 pages
File Size : 45,8 Mb
Release : 2018-09-05
Category : Electronic
ISBN : 9789176852439

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Methods and algorithms for control input placement in complex networks by Gustav Lindmark Pdf

The control-theoretic notion of controllability captures the ability to guide a systems behavior toward a desired state with a suitable choice of inputs. Controllability of complex networks such as traffic networks, gene regulatory networks, power grids etc. brings many opportunities. It could for instance enable improved efficiency in the functioning of a network or lead to that entirely new applicative possibilities emerge. However, when control theory is applied to complex networks like these, several challenges arise. This thesis consider some of these challenges, in particular we investigate how control inputs should be placed in order to render a given network controllable at a minimum cost, taking as cost function either the number of control inputs or the energy that they must exert. We assume that each control input targets only one node (called a driver node) and is either unconstrained or unilateral. A unilateral control input is one that can assume either positive or negative values but not both. Motivated by the many applications where unilateral controls are common, we reformulate classical controllability results for this particular case into a more computationally-efficient form that enables a large scale analysis. We show that the unilateral controllability problem is to a high degree structural and derive theoretical lower bounds on the minimal number of unilateral control inputs from topological properties of the network, similar to the bounds that exists for the minimal number of unconstrained control inputs. Moreover, an algorithm is developed that constructs a near minimal number of control inputs for a given network. When evaluated on various categories of random networks as well as a number of real-world networks, the algorithm often achieves the theoretical lower bounds. A network can be controllable in theory but not in practice when completely unreasonable amounts of control energy are required to steer it in some direction. For unconstrained control inputs we show that the control energy depends on the time constants of the modes of the network, and that the closer the eigenvalues are to the imaginary axis of the complex plane, the less energy is required for control. We also investigate the problem of placing driver nodes such that the control energy requirements are minimized (assuming that theoretical controllability is not an issue). For the special case with networks having all purely imaginary eigenvalues, several constructive algorithms for driver node placement are developed. In order to understand what determines the control energy in the general case with arbitrary eigenvalues, we define two centrality measures for the nodes based on energy flow considerations: the first centrality reflects the network impact of a node and the second the ability to control it indirectly. It turns out that whether a node is suitable as driver node or not largely depends on these two qualities. By combining the centralities into node rankings we obtain driver node placements that significantly reduce the control energy requirements and thereby improve the “practical degree of controllability”.

Complex Networks & Their Applications V

Hocine Cherifi,Sabrina Gaito,Walter Quattrociocchi,Alessandra Sala
Complex Networks Their Applications V Book PDF

Author : Hocine Cherifi,Sabrina Gaito,Walter Quattrociocchi,Alessandra Sala
Publisher : Springer
Page : 833 pages
File Size : 42,9 Mb
Release : 2016-11-25
Category : Technology & Engineering
ISBN : 9783319509013

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Complex Networks & Their Applications V by Hocine Cherifi,Sabrina Gaito,Walter Quattrociocchi,Alessandra Sala Pdf

This book highlights cutting-edge research in the field of network science, offering scientists, researchers and graduate students a unique opportunity to catch up on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the fifth International Workshop on Complex Networks & their Applications (COMPLEX NETWORKS 2016), which took place in Milan during the last week of November 2016. The carefully selected papers are divided into 11 sections reflecting the diversity and richness of research areas in the field. More specifically, the following topics are covered: Network models; Network measures; Community structure; Network dynamics; Diffusion, epidemics and spreading processes; Resilience and control; Network visualization; Social and political networks; Networks in finance and economics; Biological and ecological networks; and Network analysis.

Computation in Complex Networks

Clara Pizzuti,Annalisa Socievole
Computation in Complex Networks Book PDF

Author : Clara Pizzuti,Annalisa Socievole
Publisher : MDPI
Page : 352 pages
File Size : 53,6 Mb
Release : 2021-09-02
Category : Technology & Engineering
ISBN : 9783036506821

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Computation in Complex Networks by Clara Pizzuti,Annalisa Socievole Pdf

Complex networks are one of the most challenging research focuses of disciplines, including physics, mathematics, biology, medicine, engineering, and computer science, among others. The interest in complex networks is increasingly growing, due to their ability to model several daily life systems, such as technology networks, the Internet, and communication, chemical, neural, social, political and financial networks. The Special Issue “Computation in Complex Networks" of Entropy offers a multidisciplinary view on how some complex systems behave, providing a collection of original and high-quality papers within the research fields of: • Community detection • Complex network modelling • Complex network analysis • Node classification • Information spreading and control • Network robustness • Social networks • Network medicine

Advanced Methods for Complex Network Analysis

Meghanathan, Natarajan
Advanced Methods for Complex Network Analysis Book PDF

Author : Meghanathan, Natarajan
Publisher : IGI Global
Page : 461 pages
File Size : 48,9 Mb
Release : 2016-04-07
Category : Computers
ISBN : 9781466699656

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Advanced Methods for Complex Network Analysis by Meghanathan, Natarajan Pdf

As network science and technology continues to gain popularity, it becomes imperative to develop procedures to examine emergent network domains, as well as classical networks, to help ensure their overall optimization. Advanced Methods for Complex Network Analysis features the latest research on the algorithms and analysis measures being employed in the field of network science. Highlighting the application of graph models, advanced computation, and analytical procedures, this publication is a pivotal resource for students, faculty, industry practitioners, and business professionals interested in theoretical concepts and current developments in network domains.

Complex Networks & Their Applications VI

Chantal Cherifi,Hocine Cherifi,Márton Karsai,Mirco Musolesi
Complex Networks Their Applications VI Book PDF

Author : Chantal Cherifi,Hocine Cherifi,Márton Karsai,Mirco Musolesi
Publisher : Springer
Page : 1288 pages
File Size : 47,5 Mb
Release : 2017-11-24
Category : Technology & Engineering
ISBN : 9783319721507

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Complex Networks & Their Applications VI by Chantal Cherifi,Hocine Cherifi,Márton Karsai,Mirco Musolesi Pdf

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 VI International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2017), which took place in Lyon on November 29 – December 1, 2017. 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 ecological networks and technological networks.

Algorithms and Models for the Web Graph

Anthony Bonato,Fan Chung Graham,Paweł Prałat
Algorithms and Models for the Web Graph Book PDF

Author : Anthony Bonato,Fan Chung Graham,Paweł Prałat
Publisher : Springer
Page : 105 pages
File Size : 50,6 Mb
Release : 2017-09-04
Category : Computers
ISBN : 9783319678108

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Algorithms and Models for the Web Graph by Anthony Bonato,Fan Chung Graham,Paweł Prałat Pdf

This book constitutes the proceedings of the 14th International Workshop Algorithms and Models for the Web Graph, WAW 2017, held in Toronto, ON, Canada, in June 2017. The 7 full papers presented in this volume were carefully reviewed and selected from 14 submissions. The papers are organized around topics such as graphs that arise from the Web and various user activities on the Web; the development of high Performance algorithms and applications that exploit these graphs; graph-theoretic and algorithmic aspects of related complex networks; social networks, citation networks, biological networks; molecular networks, and other networks arising from the Internet.

Large Scale Structure and Dynamics of Complex Networks

Guido Caldarelli
Large Scale Structure and Dynamics of Complex Networks Book PDF

Author : Guido Caldarelli
Publisher : World Scientific
Page : 264 pages
File Size : 51,6 Mb
Release : 2007
Category : Computers
ISBN : 9789812771681

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Large Scale Structure and Dynamics of Complex Networks by Guido Caldarelli Pdf

This book is the culmination of three years of research effort on a multidisciplinary project in which physicists, mathematicians, computer scientists and social scientists worked together to arrive at a unifying picture of complex networks. The contributed chapters form a reference for the various problems in data analysis visualization and modeling of complex networks.

Big Data of Complex Networks

Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl,Andreas Holzinger
Big Data of Complex Networks Book PDF

Author : Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl,Andreas Holzinger
Publisher : CRC Press
Page : 290 pages
File Size : 45,7 Mb
Release : 2016-08-19
Category : Computers
ISBN : 9781315353593

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Big Data of Complex Networks by Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl,Andreas Holzinger Pdf

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.

Large Scale Structure and Dynamics of Complex Networks

Guido Caldarelli,Alessandro Vespignani
Large Scale Structure and Dynamics of Complex Networks Book PDF

Author : Guido Caldarelli,Alessandro Vespignani
Publisher : World Scientific
Page : 264 pages
File Size : 47,6 Mb
Release : 2007
Category : Computers
ISBN : 9789812706645

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Large Scale Structure and Dynamics of Complex Networks by Guido Caldarelli,Alessandro Vespignani Pdf

This book is the culmination of three years of research effort on a multidisciplinary project in which physicists, mathematicians, computer scientists and social scientists worked together to arrive at a unifying picture of complex networks. The contributed chapters from a reference for the various problems in data analysis visualization and modeling of complex networks.

Complex Networks VII

Hocine Cherifi,Bruno Gonçalves,Ronaldo Menezes,Roberta Sinatra
Complex Networks VII Book PDF

Author : Hocine Cherifi,Bruno Gonçalves,Ronaldo Menezes,Roberta Sinatra
Publisher : Springer
Page : 378 pages
File Size : 40,5 Mb
Release : 2016-03-10
Category : Technology & Engineering
ISBN : 9783319305691

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Complex Networks VII by Hocine Cherifi,Bruno Gonçalves,Ronaldo Menezes,Roberta Sinatra Pdf

The last decades have seen the emergence of Complex Networks as the language with which a wide range of complex phenomena in fields as diverse as Physics, Computer Science, and Medicine (to name just a few) can be properly described and understood. This book provides a view of the state of the art in this dynamic field and covers topics ranging from network controllability, social structure, online behavior, recommendation systems, and network structure. This book includes the peer-reviewed list of works presented at the 7th Workshop on Complex Networks CompleNet 2016 which was hosted by the Université de Bourgogne, France, from March 23-25, 2016. The 28 carefully reviewed and selected contributions in this book address many topics related to complex networks and have been organized in seven major groups: (1) Theory of Complex Networks, (2) Multilayer networks, (3) Controllability of networks, (4) Algorithms for networks, (5) Community detection, (6) Dynamics and spreading phenomena on networks, (7) Applications of Networks.