Computational Network Science

Download Computational Network Science full books in PDF, epub, and Kindle. Read online Computational Network Science ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Computational Network Science

Author : Henry Hexmoor
Publisher : Morgan Kaufmann
ISBN 13 : 0128011564
Total Pages : 128 pages
Book Rating : 4.1/5 (28 download)

DOWNLOAD NOW!

Book Synopsis Computational Network Science by : Henry Hexmoor

Download or read book Computational Network Science written by Henry Hexmoor and published by Morgan Kaufmann. This book was released on 2014-09-23 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Computational Network Analysis with R

Author : Matthias Dehmer
Publisher : John Wiley & Sons
ISBN 13 : 3527339582
Total Pages : 364 pages
Book Rating : 4.5/5 (273 download)

DOWNLOAD NOW!

Book Synopsis Computational Network Analysis with R by : Matthias Dehmer

Download or read book Computational Network Analysis with R written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2016-12-12 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 for R in Network Analysis.

Computational Network Theory

Author : Matthias Dehmer
Publisher : John Wiley & Sons
ISBN 13 : 3527337245
Total Pages : 278 pages
Book Rating : 4.5/5 (273 download)

DOWNLOAD NOW!

Book Synopsis Computational Network Theory by : Matthias Dehmer

Download or read book Computational Network Theory written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2015-11-16 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 homogenous style, this reference is equally suitable for courses on computational networks.

Network Science

Author : Ernesto Estrada
Publisher : Springer Science & Business Media
ISBN 13 : 1849963967
Total Pages : 249 pages
Book Rating : 4.8/5 (499 download)

DOWNLOAD NOW!

Book Synopsis Network Science by : Ernesto Estrada

Download or read book Network Science written by Ernesto Estrada and published by Springer Science & Business Media. This book was released on 2010-08-24 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network Science is the emerging field concerned with the study of large, realistic networks. This interdisciplinary endeavor, focusing on the patterns of interactions that arise between individual components of natural and engineered systems, has been applied to data sets from activities as diverse as high-throughput biological experiments, online trading information, smart-meter utility supplies, and pervasive telecommunications and surveillance technologies. This unique text/reference provides a fascinating insight into the state of the art in network science, highlighting the commonality across very different areas of application and the ways in which each area can be advanced by injecting ideas and techniques from another. The book includes contributions from an international selection of experts, providing viewpoints from a broad range of disciplines. It emphasizes networks that arise in nature—such as food webs, protein interactions, gene expression, and neural connections—and in technology—such as finance, airline transport, urban development and global trade. Topics and Features: begins with a clear overview chapter to introduce this interdisciplinary field; discusses the classic network science of fixed connectivity structures, including empirical studies, mathematical models and computational algorithms; examines time-dependent processes that take place over networks, covering topics such as synchronisation, and message passing algorithms; investigates time-evolving networks, such as the World Wide Web and shifts in topological properties (connectivity, spectrum, percolation); explores applications of complex networks in the physical and engineering sciences, looking ahead to new developments in the field. Researchers and professionals from disciplines as varied as computer science, mathematics, engineering, physics, chemistry, biology, ecology, neuroscience, epidemiology, and the social sciences will all benefit from this topical and broad overview of current activities and grand challenges in the unfolding field of network science.

Network Science

Author : Albert-László Barabási
Publisher : Cambridge University Press
ISBN 13 : 1107076269
Total Pages : 477 pages
Book Rating : 4.1/5 (7 download)

DOWNLOAD NOW!

Book Synopsis Network Science by : Albert-László Barabási

Download or read book Network Science written by Albert-László Barabási and published by Cambridge University Press. This book was released on 2016-07-21 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: Illustrated throughout in full colour, this pioneering text is the only book you need for an introduction to network science.

A First Course in Network Science

Author : Filippo Menczer
Publisher : Cambridge University Press
ISBN 13 : 1108579612
Total Pages : 275 pages
Book Rating : 4.1/5 (85 download)

DOWNLOAD NOW!

Book Synopsis A First Course in Network Science by : Filippo Menczer

Download or read book A First Course in Network Science written by Filippo Menczer and published by Cambridge University Press. This book was released on 2020-01-30 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.

Network Models for Data Science

Author : Alan Julian Izenman
Publisher : Cambridge University Press
ISBN 13 : 1108889034
Total Pages : 502 pages
Book Rating : 4.1/5 (88 download)

DOWNLOAD NOW!

Book Synopsis Network Models for Data Science by : Alan Julian Izenman

Download or read book Network Models for Data Science written by Alan Julian Izenman and published by Cambridge University Press. This book was released on 2023-01-05 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text on the theory and applications of network science is aimed at beginning graduate students in statistics, data science, computer science, machine learning, and mathematics, as well as advanced students in business, computational biology, physics, social science, and engineering working with large, complex relational data sets. It provides an exciting array of analysis tools, including probability models, graph theory, and computational algorithms, exposing students to ways of thinking about types of data that are different from typical statistical data. Concepts are demonstrated in the context of real applications, such as relationships between financial institutions, between genes or proteins, between neurons in the brain, and between terrorist groups. Methods and models described in detail include random graph models, percolation processes, methods for sampling from huge networks, network partitioning, and community detection. In addition to static networks the book introduces dynamic networks such as epidemics, where time is an important component.

Network Science In Education

Author : Catherine B. Cramer
Publisher : Springer
ISBN 13 : 3319772376
Total Pages : 205 pages
Book Rating : 4.3/5 (197 download)

DOWNLOAD NOW!

Book Synopsis Network Science In Education by : Catherine B. Cramer

Download or read book Network Science In Education written by Catherine B. Cramer and published by Springer. This book was released on 2018-10-22 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Around the globe, there is an increasingly urgent need to provide opportunities for learners to embrace complexity; to develop the many skills and habits of mind that are relevant to today's complex and interconnected world; and to make learning more connected to our rapidly changing workplace and society. This presents an opportunity to (1) leverage new paradigms for understanding the structure and function of teaching and learning communities, and (2) to promote new approaches to developing methods, curricular materials, and resources. Network science - the study of connectivity - can play an important role in these activities, both as an important subject in teaching and learning and as a way to develop interconnected curricula. Since 2010, an international community of network science researchers and educators has come together to raise the global level of network literacy by applying ideas from network science to teaching and learning. Network Science in Education - which refers to both this community and to its activities - has evolved in response to the escalating activity in the field of network science and the need for people to be able to access the field through education channels. Network Science In Education: Transformational Approaches in Teaching and Learning appeals to both instructors and professionals, while offering case studies from a wide variety of activities that have been developed around the globe: the creation of entirely new courses and degree programs; tools for K-20 learners, teachers, and the general public; and in-depth analysis of selected programs. As network-based pedagogy and the community of practice continues to grow, we hope that the book's readers will join this vibrant network education community to build on these nascent ideas and help deepen the understanding of networks for all learners.

Computational Thinking: A Perspective on Computer Science

Author : Zhiwei Xu
Publisher : Springer Nature
ISBN 13 : 9811638489
Total Pages : 338 pages
Book Rating : 4.8/5 (116 download)

DOWNLOAD NOW!

Book Synopsis Computational Thinking: A Perspective on Computer Science by : Zhiwei Xu

Download or read book Computational Thinking: A Perspective on Computer Science written by Zhiwei Xu and published by Springer Nature. This book was released on 2022-01-01 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is intended as a textbook for one-semester, introductory computer science courses aimed at undergraduate students from all disciplines. Self-contained and with no prerequisites, it focuses on elementary knowledge and thinking models. The content has been tested in university classrooms for over six years, and has been used in summer schools to train university and high-school teachers on teaching introductory computer science courses using computational thinking. This book introduces computer science from a computational thinking perspective. In computer science the way of thinking is characterized by three external and eight internal features, including automatic execution, bit-accuracy and abstraction. The book is divided into chapters on logic thinking, algorithmic thinking, systems thinking, and network thinking. It also covers societal impact and responsible computing material – from ICT industry to digital economy, from the wonder of exponentiation to wonder of cyberspace, and from code of conduct to best practices for independent work. The book’s structure encourages active, hands-on learning using the pedagogic tool Bloom's taxonomy to create computational solutions to over 200 problems of varying difficulty. Students solve problems using a combination of thought experiment, programming, and written methods. Only 300 lines of code in total are required to solve most programming problems in this book.

Introduction to Computational Social Science

Author : Claudio Cioffi-Revilla
Publisher : Springer
ISBN 13 : 3319501313
Total Pages : 636 pages
Book Rating : 4.3/5 (195 download)

DOWNLOAD NOW!

Book Synopsis Introduction to Computational Social Science by : Claudio Cioffi-Revilla

Download or read book Introduction to Computational Social Science written by Claudio Cioffi-Revilla and published by Springer. This book was released on 2017-06-29 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 more than a thousand questions and exercises, together with a list of acronyms and a glossary; examines the similarities and differences between computers and social systems; presents a focus on automated information extraction; discusses the measurement, scientific laws, and generative theories of social complexity in CSS; reviews the methodology of social simulations, covering both variable- and object-oriented models.

Computational Systems Biology

Author : Paola Lecca
Publisher : Woodhead Publishing
ISBN 13 : 0081001150
Total Pages : 180 pages
Book Rating : 4.0/5 (81 download)

DOWNLOAD NOW!

Book Synopsis Computational Systems Biology by : Paola Lecca

Download or read book Computational Systems Biology written by Paola Lecca and published by Woodhead Publishing. This book was released on 2016-07-29 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Systems Biology: Inference and Modelling provides an introduction to, and overview of, network analysis inference approaches which form the backbone of the model of the complex behavior of biological systems. This book addresses the challenge to integrate highly diverse quantitative approaches into a unified framework by highlighting the relationships existing among network analysis, inference, and modeling. The chapters are light in jargon and technical detail so as to make them accessible to the non-specialist reader. The book is addressed at the heterogeneous public of modelers, biologists, and computer scientists. Provides a unified presentation of network inference, analysis, and modeling Explores the connection between math and systems biology, providing a framework to learn to analyze, infer, simulate, and modulate the behavior of complex biological systems Includes chapters in modular format for learning the basics quickly and in the context of questions posed by systems biology Offers a direct style and flexible formalism all through the exposition of mathematical concepts and biological applications

Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining

Author : Nitin Agarwal
Publisher : Springer
ISBN 13 : 9783030067977
Total Pages : 0 pages
Book Rating : 4.0/5 (679 download)

DOWNLOAD NOW!

Book Synopsis Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining by : Nitin Agarwal

Download or read book Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining written by Nitin Agarwal and published by Springer. This book was released on 2018-12-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributors in this book share, exchange, and develop new concepts, ideas, principles, and methodologies in order to advance and deepen our understanding of social networks in the new generation of Information and Communication Technologies (ICT) enabled by Web 2.0, also referred to as social media, to help policy-making. This interdisciplinary work provides a platform for researchers, practitioners, and graduate students from sociology, behavioral science, computer science, psychology, cultural studies, information systems, operations research and communication to share, exchange, learn, and develop new concepts, ideas, principles, and methodologies. Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining will be of interest to researchers, practitioners, and graduate students from the various disciplines listed above. The text facilitates the dissemination of investigations of the dynamics and structure of web based social networks. The book can be used as a reference text for advanced courses on Social Network Analysis, Sociology, Communication, Organization Theory, Cyber-anthropology, Cyber-diplomacy, and Information Technology and Justice.

An Introduction to Computational Learning Theory

Author : Michael J. Kearns
Publisher : MIT Press
ISBN 13 : 9780262111935
Total Pages : 230 pages
Book Rating : 4.1/5 (119 download)

DOWNLOAD NOW!

Book Synopsis An Introduction to Computational Learning Theory by : Michael J. Kearns

Download or read book An Introduction to Computational Learning Theory written by Michael J. Kearns and published by MIT Press. This book was released on 1994-08-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.

Computational Problems in Science and Engineering

Author : Nikos Mastorakis
Publisher : Springer
ISBN 13 : 3319157655
Total Pages : 491 pages
Book Rating : 4.3/5 (191 download)

DOWNLOAD NOW!

Book Synopsis Computational Problems in Science and Engineering by : Nikos Mastorakis

Download or read book Computational Problems in Science and Engineering written by Nikos Mastorakis and published by Springer. This book was released on 2015-10-26 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with modern computational techniques for solving variety of problems from electrical, mechanical, civil and chemical engineering. Mathematical methods are presented in a unified manner, so they can be applied consistently to problems in applied electromagnetics, strength of materials, fluid mechanics, heat and mass transfer, environmental engineering, biomedical engineering, signal processing, automatic control and more.

Analyzing Network Data in Biology and Medicine

Author : Nataša Pržulj
Publisher : Cambridge University Press
ISBN 13 : 1108432239
Total Pages : 647 pages
Book Rating : 4.1/5 (84 download)

DOWNLOAD NOW!

Book Synopsis Analyzing Network Data in Biology and Medicine by : Nataša Pržulj

Download or read book Analyzing Network Data in Biology and Medicine written by Nataša Pržulj and published by Cambridge University Press. This book was released on 2019-03-28 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.

Essential Computational Thinking

Author : Ricky J. Sethi
Publisher : Cognella Academic Publishing
ISBN 13 : 1516583213
Total Pages : 328 pages
Book Rating : 4.5/5 (165 download)

DOWNLOAD NOW!

Book Synopsis Essential Computational Thinking by : Ricky J. Sethi

Download or read book Essential Computational Thinking written by Ricky J. Sethi and published by Cognella Academic Publishing. This book was released on 2020-06-17 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essential Computational Thinking: Computer Science from Scratch helps students build a theoretical and practical foundation for learning computer science. Rooted in fundamental science, this text defines elementary ideas including data and information, quantifies these ideas mathematically, and, through key concepts in physics and computation, demonstrates the relationship between computer science and the universe itself. In Part I, students explore the theoretical underpinnings of computer science in a wide-ranging manner. Readers receive a robust overview of essential computational theories and programming ideas, as well as topics that examine the mathematical and physical foundations of computer science. Part 2 presents the basics of computation and underscores programming as an invaluable tool in the discipline. Students can apply their newfound knowledge and begin writing substantial programs immediately. Finally, Part 3 explores more sophisticated computational ideas, including object-oriented programing, databases, data science, and some of the underlying principles of machine learning. Essential Computational Thinking is an ideal text for a firmly technical CS0 course in computer science. It is also a valuable resource for highly-motivated non-computer science majors at the undergraduate or graduate level who are interested in learning more about the discipline for either professional or personal development.

Network Science in Cognitive Psychology

Author : Michael S. Vitevitch
Publisher : Routledge
ISBN 13 : 1000740684
Total Pages : 213 pages
Book Rating : 4.0/5 (7 download)

DOWNLOAD NOW!

Book Synopsis Network Science in Cognitive Psychology by : Michael S. Vitevitch

Download or read book Network Science in Cognitive Psychology written by Michael S. Vitevitch and published by Routledge. This book was released on 2019-11-26 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides an integrative review of the emerging and increasing use of network science techniques in cognitive psychology, first developed in mathematics, computer science, sociology, and physics. The first resource on network science for cognitive psychologists in a growing international market, Vitevitch and a team of expert contributors provide a comprehensive and accessible overview of this cutting-edge topic. This innovative guide draws on the three traditional pillars of cognitive psychological research–experimental, computational, and neuroscientific–and incorporates the latest findings from neuroimaging. The network perspective is applied to the fundamental domains of cognitive psychology including memory, language, problem-solving, and learning, as well as creativity and human intelligence, highlighting the insights to be gained through applying network science to a wide range of approaches and topics in cognitive psychology Network Science in Cognitive Psychology will be essential reading for all upper-level cognitive psychology students, psychological researchers interested in using network science in their work, and network scientists interested in investigating questions related to cognition. It will also be useful for early career researchers and students in methodology and related courses.