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

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.

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

Complex Networks

Complex Networks
  • Author : Vito Latora,Vincenzo Nicosia,Giovanni Russo
  • Publisher : Cambridge University Press
  • Release : 30 September 2017
GET THIS BOOKComplex Networks

A comprehensive introduction to the theory and applications of complex network science, complete with real-world data sets and software tools.

Introduction to Computational Social Science

Introduction to Computational Social Science
  • Author : Claudio Cioffi-Revilla
  • Publisher : Springer
  • Release : 29 June 2017
GET THIS BOOKIntroduction to Computational Social Science

This textbook provides a comprehensive and reader-friendly introduction to the field of computational social science (CSS). Presenting a unified treatment, the text examines in detail the four key methodological approaches of automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. This updated new edition has been enhanced with numerous review questions and exercises to test what has been learned, deepen understanding through problem-solving, and to practice writing code to implement ideas. Topics and features: contains

Computational Network Theory

Computational Network Theory
  • Author : Matthias Dehmer,Frank Emmert-Streib,Stefan Pickl
  • Publisher : John Wiley & Sons
  • Release : 04 May 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 a tool 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

Probabilistic Networks and Expert Systems

Probabilistic Networks and Expert Systems
  • Author : Robert G. Cowell,Philip Dawid,Steffen L. Lauritzen,David J. Spiegelhalter
  • Publisher : Springer Science & Business Media
  • Release : 16 July 2007
GET THIS BOOKProbabilistic Networks and Expert Systems

The work reviewed in this book represents the synthesis of two important developments in modelling of complex stochastic phenomena. The book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms.

Temporal Network Theory

Temporal Network Theory
  • Author : Petter Holme,Jari Saramäki
  • Publisher : Springer Nature
  • Release : 29 October 2019
GET THIS BOOKTemporal Network Theory

This book focuses on the theoretical side of temporal network research and gives an overview of the state of the art in the field. Curated by two pioneers in the field who have helped to shape it, the book contains contributions from many leading researchers. Temporal networks fill the border area between network science and time-series analysis and are relevant for the modeling of epidemics, optimization of transportation and logistics, as well as understanding biological phenomena. Network theory has proven,

Computational Social Network Analysis

Computational Social Network Analysis
  • Author : Ajith Abraham,Aboul-Ella Hassanien,Vaclav Snášel
  • Publisher : Springer Science & Business Media
  • Release : 10 December 2009
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

Complex Networks & Their Applications VI

Complex Networks & Their Applications VI
  • Author : Chantal Cherifi,Hocine Cherifi,Márton Karsai,Mirco Musolesi
  • Publisher : Springer
  • Release : 24 November 2017
GET THIS BOOKComplex Networks & Their Applications VI

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

Network Science and Cybersecurity

Network Science and Cybersecurity
  • Author : Robinson E. Pino
  • Publisher : Springer Science & Business Media
  • Release : 14 June 2013
GET THIS BOOKNetwork Science and Cybersecurity

Network Science and Cybersecurity introduces new research and development efforts for cybersecurity solutions and applications taking place within various U.S. Government Departments of Defense, industry and academic laboratories. This book examines new algorithms and tools, technology platforms and reconfigurable technologies for cybersecurity systems. Anomaly-based intrusion detection systems (IDS) are explored as a key component of any general network intrusion detection service, complementing signature-based IDS components by attempting to identify novel attacks. These attacks may not yet be known or

Computational Social Science

Computational Social Science
  • Author : R. Michael Alvarez
  • Publisher : Cambridge University Press
  • Release : 07 March 2016
GET THIS BOOKComputational Social Science

Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extraordinary work being conducted in computational social