Computational Network Science

The emerging field of network science represents a new style of research that can unify such traditionally-diverse fields as sociology, economics, physics, biology, and computer science. It is a powerful tool in analyzing both natural and man-made systems, using the relationships between players within these networks and between the networks themselves to gain insight into the nature of each field. Until now, studies in network science have been focused on particular relationships that require varied and sometimes-incompatible datasets, which has kept it from being a truly universal discipline. Computational Network Science seeks to unify the methods used to analyze these diverse fields. This book provides an introduction to the field of Network Science and provides the groundwork for a computational, algorithm-based approach to network and system analysis in a new and important way. This new approach would remove the need for tedious human-based analysis of different datasets and help researchers spend more time on the qualitative aspects of network science research. Demystifies media hype regarding Network Science and serves as a fast-paced introduction to state-of-the-art concepts and systems related to network science Comprehensive coverage of Network Science algorithms, methodologies, and common problems Includes references to formative and updated developments in the field Coverage spans mathematical sociology, economics, political science, and biological networks

Produk Detail:

  • Author : Henry Hexmoor
  • Publisher : Morgan Kaufmann
  • Pages : 128 pages
  • ISBN : 0128011564
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKComputational Network Science

Computational Network Science

Computational Network Science
  • Author : Henry Hexmoor
  • Publisher : Morgan Kaufmann
  • Release : 23 September 2014
GET THIS BOOKComputational Network Science

The emerging field of network science represents a new style of research that can unify such traditionally-diverse fields as sociology, economics, physics, biology, and computer science. It is a powerful tool in analyzing both natural and man-made systems, using the relationships between players within these networks and between the networks themselves to gain insight into the nature of each field. Until now, studies in network science have been focused on particular relationships that require varied and sometimes-incompatible datasets, which has

Computational Network Analysis with R

Computational Network Analysis with R
  • Author : Matthias Dehmer,Yongtang Shi,Frank Emmert-Streib
  • Publisher : John Wiley & Sons
  • Release : 12 December 2016
GET THIS BOOKComputational Network Analysis with R

This new title in the well-established "Quantitative Network Biology" series includes innovative and existing methods for analyzing network data in such areas as network biology and chemoinformatics. With its easy-to-follow introduction to the theoretical background and application-oriented chapters, the book demonstrates that R is a powerful language for statistically analyzing networks and for solving such large-scale phenomena as network sampling and bootstrapping. Written by editors and authors with an excellent track record in the field, this is the ultimate reference

Computational Network Theory

Computational Network Theory
  • Author : Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl
  • Publisher : John Wiley & Sons
  • Release : 02 November 2015
GET THIS BOOKComputational Network Theory

This comprehensive introduction to computational network theory as a branch of network theory builds on the understanding that such networks are important tools to derive or verify hypotheses by applying computational techniques to large scale network data. The highly experienced team of editors and high-profile authors from around the world present and explain a number of methods that are representative of computational network theory, derived from graph theory, as well as computational and statistical techniques. With its coherent structure and

Computational Network Science

Computational Network Science
  • Author : Henry Hexmoor
  • Publisher : Morgan Kaufmann
  • Release : 29 September 2014
GET THIS BOOKComputational Network Science

The emerging field of network science represents a new style of research that can unify such traditionally-diverse fields as sociology, economics, physics, biology, and computer science. It is a powerful tool in analyzing both natural and man-made systems, using the relationships between players within these networks and between the networks themselves to gain insight into the nature of each field. Until now, studies in network science have been focused on particular relationships that require varied and sometimes-incompatible datasets, which has

Computational Social Network Analysis

Computational Social Network Analysis
  • Author : Ajith Abraham,Aboul-Ella Hassanien,Vaclav Snášel
  • Publisher : Springer
  • Release : 01 March 2012
GET THIS BOOKComputational Social Network Analysis

Social networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Web 2.0 has enabled a new generation of web-based communities, social networks, and folksonomies to facilitate collaboration among different communities. This unique text/reference compares and contrasts the ethological approach to social behavior in animals with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans and affinities between web-based social networks. An international team of leading experts present

Network Science

Network Science
  • Author : Albert-László Barabási
  • Publisher : Cambridge University Press
  • Release : 21 July 2016
GET THIS BOOKNetwork Science

Illustrated throughout in full colour, this pioneering text is the only book you need for an introduction to network science.

The Oxford Handbook of Social Networks

The Oxford Handbook of Social Networks
  • Author : Ryan Light,James Moody
  • Publisher : Oxford University Press
  • Release : 20 November 2020
GET THIS BOOKThe Oxford Handbook of Social Networks

While some social scientists may argue that we have always been networked, the increased visibility of networks today across economic, political, and social domains can hardly be disputed. Social networks fundamentally shape our lives and social network analysis has become a vibrant, interdisciplinary field of research. In The Oxford Handbook of Social Networks, Ryan Light and James Moody have gathered forty leading scholars in sociology, archaeology, economics, statistics, and information science, among others, to provide an overview of the theory,

Biological Network Analysis

Biological Network Analysis
  • Author : Pietro Hiram Guzzi,Swarup Roy
  • Publisher : Elsevier
  • Release : 11 May 2020
GET THIS BOOKBiological Network Analysis

Biological Network Analysis: Trends, Approaches, Graph Theory, and Algorithms considers three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN), and Human Brain Connectomes. The book's authors discuss various graph theoretic and data analytics approaches used to analyze these networks with respect to available tools, technologies, standards, algorithms and databases for generating, representing and analyzing graphical data. As a wide variety of algorithms have been developed to analyze and compare networks, this book is a timely resource.

Agent-Based Modeling and Network Dynamics

Agent-Based Modeling and Network Dynamics
  • Author : Akira Namatame,Shu-Heng Chen
  • Publisher : Oxford University Press
  • Release : 28 January 2016
GET THIS BOOKAgent-Based Modeling and Network Dynamics

While the significance of networks in various human behavior and activities has a history as long as human's existence, network awareness is a recent scientific phenomenon. The neologism network science is just one or two decades old. Nevertheless, with this limited time, network thinking has substantially reshaped the recent development in economics, and almost all solutions to real-world problems involve the network element. This book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary

Complex Networks

Complex Networks
  • Author : Kayhan Erciyes
  • Publisher : CRC Press
  • Release : 06 September 2014
GET THIS BOOKComplex Networks

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 structures of complex networks, few books focus on the algorithmic aspects of complex network analysis. Filling this need, Complex Networks: An Algorithmic Perspective supplies the basic theoretical

Recent Trends in Computational Intelligence Enabled Research

Recent Trends in Computational Intelligence Enabled Research
  • Author : Siddhartha Bhattacharyya,Paramartha Dutta,Debabrata Samanta,Anirban Mukherjee,Indrajit Pan
  • Publisher : Academic Press
  • Release : 31 July 2021
GET THIS BOOKRecent Trends in Computational Intelligence Enabled Research

The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With

Computational Neural Networks for Geophysical Data Processing

Computational Neural Networks for Geophysical Data Processing
  • Author : M.M. Poulton
  • Publisher : Elsevier
  • Release : 13 June 2001
GET THIS BOOKComputational Neural Networks for Geophysical Data Processing

This book was primarily written for an audience that has heard about neural networks or has had some experience with the algorithms, but would like to gain a deeper understanding of the fundamental material. For those that already have a solid grasp of how to create a neural network application, this work can provide a wide range of examples of nuances in network design, data set design, testing strategy, and error analysis. Computational, rather than artificial, modifiers are used for