Mining Complex Networks

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Publisher : CRC Press
ISBN 13 : 1000515850
Total Pages : 278 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Mining Complex Networks by : Bogumil Kaminski

Download or read book Mining Complex Networks written by Bogumil Kaminski and published by CRC Press. This book was released on 2021-12-14 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Mining Complex Networks

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Author :
Publisher : CRC Press
ISBN 13 : 1000515907
Total Pages : 228 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Mining Complex Networks by : Bogumil Kaminski

Download or read book Mining Complex Networks written by Bogumil Kaminski and published by CRC Press. This book was released on 2021-12-14 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Graph Spectra for Complex Networks

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Author :
Publisher : Cambridge University Press
ISBN 13 : 1139492276
Total Pages : 363 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Graph Spectra for Complex Networks by : Piet van Mieghem

Download or read book Graph Spectra for Complex Networks written by Piet van Mieghem and published by Cambridge University Press. This book was released on 2010-12-02 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyzing the behavior of complex networks is an important element in the design of new man-made structures such as communication systems and biologically engineered molecules. Because any complex network can be represented by a graph, and therefore in turn by a matrix, graph theory has become a powerful tool in the investigation of network performance. This self-contained 2010 book provides a concise introduction to the theory of graph spectra and its applications to the study of complex networks. Covering a range of types of graphs and topics important to the analysis of complex systems, this guide provides the mathematical foundation needed to understand and apply spectral insight to real-world systems. In particular, the general properties of both the adjacency and Laplacian spectrum of graphs are derived and applied to complex networks. An ideal resource for researchers and students in communications networking as well as in physics and mathematics.

Machine Learning in Complex Networks

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Publisher : Springer
ISBN 13 : 3319172905
Total Pages : 345 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Machine Learning in Complex Networks by : Thiago Christiano Silva

Download or read book Machine Learning in Complex Networks written by Thiago Christiano Silva and published by Springer. This book was released on 2016-01-28 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the features and advantages offered by complex networks in the machine learning domain. In the first part, an overview on complex networks and network-based machine learning is presented, offering necessary background material. In the second part, we describe in details some specific techniques based on complex networks for supervised, non-supervised, and semi-supervised learning. Particularly, a stochastic particle competition technique for both non-supervised and semi-supervised learning using a stochastic nonlinear dynamical system is described in details. Moreover, an analytical analysis is supplied, which enables one to predict the behavior of the proposed technique. In addition, data reliability issues are explored in semi-supervised learning. Such matter has practical importance and is not often found in the literature. With the goal of validating these techniques for solving real problems, simulations on broadly accepted databases are conducted. Still in this book, we present a hybrid supervised classification technique that combines both low and high orders of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features, while the latter measures the compliance of the test instances with the pattern formation of the data. We show that the high level technique can realize classification according to the semantic meaning of the data. This book intends to combine two widely studied research areas, machine learning and complex networks, which in turn will generate broad interests to scientific community, mainly to computer science and engineering areas.

Structural Analysis of Complex Networks

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Publisher : Springer Science & Business Media
ISBN 13 : 0817647899
Total Pages : 493 pages
Book Rating : 4.8/5 (176 download)

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Book Synopsis Structural Analysis of Complex Networks by : Matthias Dehmer

Download or read book Structural Analysis of Complex Networks written by Matthias Dehmer and published by Springer Science & Business Media. This book was released on 2010-10-14 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science, machine learning, artificial intelligence, computational and systems biology, cognitive science, computational linguistics, and mathematical chemistry. It may also be used as a supplementary textbook in graduate-level seminars on structural graph analysis, complex networks, or network-based machine learning methods.

Graph Mining

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Publisher : Morgan & Claypool Publishers
ISBN 13 : 160845116X
Total Pages : 209 pages
Book Rating : 4.6/5 (84 download)

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Book Synopsis Graph Mining by : Deepayan Chakrabarti

Download or read book Graph Mining written by Deepayan Chakrabarti and published by Morgan & Claypool Publishers. This book was released on 2012-10-01 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important, because they can help with "what if" scenarios, extrapolations, and anonymization. Then we provide a list of powerful tools for graph analysis, and specifically spectral methods (Singular Value Decomposition (SVD)), tensors, and case studies like the famous "pageRank" algorithm and the "HITS" algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology, which provide complementary viewpoints. Table of Contents: Introduction / Patterns in Static Graphs / Patterns in Evolving Graphs / Patterns in Weighted Graphs / Discussion: The Structure of Specific Graphs / Discussion: Power Laws and Deviations / Summary of Patterns / Graph Generators / Preferential Attachment and Variants / Incorporating Geographical Information / The RMat / Graph Generation by Kronecker Multiplication / Summary and Practitioner's Guide / SVD, Random Walks, and Tensors / Tensors / Community Detection / Influence/Virus Propagation and Immunization / Case Studies / Social Networks / Other Related Work / Conclusions

Mining Dynamic Structures in Complex Networks

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Publisher :
ISBN 13 :
Total Pages : 65 pages
Book Rating : 4.:/5 (466 download)

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Book Synopsis Mining Dynamic Structures in Complex Networks by : Scott J. McCallen

Download or read book Mining Dynamic Structures in Complex Networks written by Scott J. McCallen and published by . This book was released on 2007 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex networks have attracted much attention across many scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Most of the studies have mainly focused on the topology of the network. However, in many real world applications, the edges and vertices have associated attributes that are frequently represented as edge or vertex weights. Furthermore, these weights are often not static, instead changing with time and forming a time series. Hence, to fully understand the dynamics of a complex network, we must consider both topology and related time series data. Despite the rapid accumulation of such data, understanding the dynamic nature of complex networks remains a complicated and mostly unexplored task. In this work, we propose two novel mining approaches to identify dynamic structures that account for both temporal and topological characteristics in complex networks. The first approach is the definition and identification of time series trends and trend motifs. A trend motif describes a recurring subgraph where all of its vertices or edges display similar temporal trends. Given this, each occurrence can help reveal significant events in a complex system and frequent motifs may aid in uncovering dynamic rules of change for the system. In our second approach, we define the dynamic module, which expands and improves upon our first model. Essentially, a dynamic module is a set of connected vertices where the time series associated with each vertex forms certain structures in the temporal domain. We have developed efficient mining algorithms to extract these interesting dynamic structures and our experimental validation using datasets ranging from the stock market, world trade, to a protein interaction network, has demonstrated the efficiency and effectiveness of our approach.

Handbook of Optimization in Complex Networks

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Publisher : Springer Science & Business Media
ISBN 13 : 1461408571
Total Pages : 539 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Handbook of Optimization in Complex Networks by : My T. Thai

Download or read book Handbook of Optimization in Complex Networks written by My T. Thai and published by Springer Science & Business Media. This book was released on 2011-11-25 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences. Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network. Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks. A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

Social Network Mining, Analysis, and Research Trends: Techniques and Applications

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Publisher : IGI Global
ISBN 13 : 1613505140
Total Pages : 430 pages
Book Rating : 4.6/5 (135 download)

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Book Synopsis Social Network Mining, Analysis, and Research Trends: Techniques and Applications by : Ting, I-Hsien

Download or read book Social Network Mining, Analysis, and Research Trends: Techniques and Applications written by Ting, I-Hsien and published by IGI Global. This book was released on 2011-12-31 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book covers current research trends in the area of social networks analysis and mining, sharing research from experts in the social network analysis and mining communities, as well as practitioners from social science, business, and computer science"--Provided by publisher.

Computational Social Networks

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Publisher : Springer Science & Business Media
ISBN 13 : 1447140486
Total Pages : 474 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Computational Social Networks by : Ajith Abraham

Download or read book Computational Social Networks written by Ajith Abraham and published by Springer Science & Business Media. This book was released on 2012-06-28 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, with a specific focus on practical tools, applications, and open avenues for further research (the other two volumes review issues of Security and Privacy, and Mining and Visualization in CSNs). Topics and features: presents the latest advances in CSNs, and illustrates how organizations can gain a competitive advantage by applying these ideas in real-world scenarios; discusses the design and use of a wide range of computational tools and software for social network analysis; describes simulations of social networks, the representation and analysis of social networks, and the use of semantic networks in knowledge discovery and visualization; provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology.

Advances in Social Network Mining and Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 3642149286
Total Pages : 141 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Advances in Social Network Mining and Analysis by : C. Lee Giles

Download or read book Advances in Social Network Mining and Analysis written by C. Lee Giles and published by Springer Science & Business Media. This book was released on 2010-08-10 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work constitutes the proceedings of the Second International Workshop on Advances in Social Network and Analysis, held in Las Vegas, NV, USA in August 2008.

Graph Theory and Complex Networks

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Publisher : Maarten Van Steen
ISBN 13 : 9789081540612
Total Pages : 285 pages
Book Rating : 4.5/5 (46 download)

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Book Synopsis Graph Theory and Complex Networks by : Maarten van Steen

Download or read book Graph Theory and Complex Networks written by Maarten van Steen and published by Maarten Van Steen. This book was released on 2010 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to explain the basics of graph theory that are needed at an introductory level for students in computer or information sciences. To motivate students and to show that even these basic notions can be extremely useful, the book also aims to provide an introduction to the modern field of network science. Mathematics is often unnecessarily difficult for students, at times even intimidating. For this reason, explicit attention is paid in the first chapters to mathematical notations and proof techniques, emphasizing that the notations form the biggest obstacle, not the mathematical concepts themselves. This approach allows to gradually prepare students for using tools that are necessary to put graph theory to work: complex networks. In the second part of the book the student learns about random networks, small worlds, the structure of the Internet and the Web, peer-to-peer systems, and social networks. Again, everything is discussed at an elementary level, but such that in the end students indeed have the feeling that they: 1.Have learned how to read and understand the basic mathematics related to graph theory. 2.Understand how basic graph theory can be applied to optimization problems such as routing in communication networks. 3.Know a bit more about this sometimes mystical field of small worlds and random networks. There is an accompanying web site www.distributed-systems.net/gtcn from where supplementary material can be obtained, including exercises, Mathematica notebooks, data for analyzing graphs, and generators for various complex networks.

Complex Systems and Networks

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Publisher : Springer
ISBN 13 : 3662478242
Total Pages : 483 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis Complex Systems and Networks by : Jinhu Lü

Download or read book Complex Systems and Networks written by Jinhu Lü and published by Springer. This book was released on 2015-08-14 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of complex networks provide some applicable carriers, which show the importance of theories developed in complex networks. In particular, a general model for studying time evolution of transition networks, deflection routing in complex networks, recommender systems for social networks analysis and mining, strategy selection in networked evolutionary games, integration and methods in computational biology, are discussed in detail.

Mining Complex Data

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Publisher : Springer Science & Business Media
ISBN 13 : 3540880666
Total Pages : 300 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Mining Complex Data by : Djamel A. Zighed

Download or read book Mining Complex Data written by Djamel A. Zighed and published by Springer Science & Business Media. This book was released on 2008-10-13 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to gather the most recent works that address issues related to the concept of mining complex data. The whole knowledge discovery process being involved, our goal is to provide researchers dealing with each step of this process by key entries. Actually, managing complex data within the KDD process implies to work on every step, starting from the pre-processing (e.g. structuring and organizing) to the visualization and interpretation (e.g. sorting or filtering) of the results, via the data mining methods themselves (e.g. classification, clustering, frequent patterns extraction, etc.). The papers presented here are selected from the workshop papers held yearly since 2006.

Complex Networks & Their Applications VI

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Publisher : Springer
ISBN 13 : 331972150X
Total Pages : 1290 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Complex Networks & Their Applications VI by : Chantal Cherifi

Download or read book Complex Networks & Their Applications VI written by Chantal Cherifi and published by Springer. This book was released on 2017-11-24 with total page 1290 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Encyclopedia of Social Network Analysis and Mining

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Publisher : Springer
ISBN 13 : 9781493971305
Total Pages : 0 pages
Book Rating : 4.9/5 (713 download)

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Book Synopsis Encyclopedia of Social Network Analysis and Mining by : Reda Alhajj

Download or read book Encyclopedia of Social Network Analysis and Mining written by Reda Alhajj and published by Springer. This book was released on 2018-05-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of Social Network Analysis and Mining (ESNAM) is the first major reference work to integrate fundamental concepts and research directions in the areas of social networks and applications to data mining. The second edition of ESNAM is a truly outstanding reference appealing to researchers, practitioners, instructors and students (both undergraduate and graduate), as well as the general public. This updated reference integrates all basics concepts and research efforts under one umbrella. Coverage has been expanded to include new emerging topics such as crowdsourcing, opinion mining, and sentiment analysis. Revised content of existing material keeps the encyclopedia current. The second edition is intended for college students as well as public and academic libraries. It is anticipated to continue to stimulate more awareness of social network applications and research efforts. The advent of electronic communication, and in particular on-line communities, have created social networks of hitherto unimaginable sizes. Reflecting the interdisciplinary nature of this unique field, the essential contributions of diverse disciplines, from computer science, mathematics, and statistics to sociology and behavioral science, are described among the 300 authoritative yet highly readable entries. Students will find a world of information and insight behind the familiar façade of the social networks in which they participate. Researchers and practitioners will benefit from a comprehensive perspective on the methodologies for analysis of constructed networks, and the data mining and machine learning techniques that have proved attractive for sophisticated knowledge discovery in complex applications. Also addressed is the application of social network methodologies to other domains, such as web networks and biological networks.

Random Graphs and Complex Networks

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Publisher : Cambridge University Press
ISBN 13 : 110717287X
Total Pages : 341 pages
Book Rating : 4.1/5 (71 download)

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Book Synopsis Random Graphs and Complex Networks by : Remco van der Hofstad

Download or read book Random Graphs and Complex Networks written by Remco van der Hofstad and published by Cambridge University Press. This book was released on 2017 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classroom-tested text is the definitive introduction to the mathematics of network science, featuring examples and numerous exercises.