Machine Learning In Complex Networks
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Machine Learning In Complex Networks
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Author : Thiago Christiano Silva
language : en
Publisher: Springer
Release Date : 2016-02-11
Machine Learning In Complex Networks written by Thiago Christiano Silva and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-11 with Computers categories.
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.
Machine Learning In Social Networks
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Author : Manasvi Aggarwal
language : en
Publisher:
Release Date : 2021
Machine Learning In Social Networks written by Manasvi Aggarwal and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
This book deals with network representation learning. It deals with embedding nodes, edges, subgraphs and graphs. There is a growing interest in understanding complex systems in different domains including health, education, agriculture and transportation. Such complex systems are analyzed by modeling, using networks that are aptly called complex networks. Networks are becoming ubiquitous as they can represent many real-world relational data, for instance, information networks, molecular structures, telecommunication networks and protein-protein interaction networks. Analysis of these networks provides advantages in many fields such as recommendation (recommending friends in a social network), biological field (deducing connections between proteins for treating new diseases) and community detection (grouping users of a social network according to their interests) by leveraging the latent information of networks. An active and important area of current interest is to come out with algorithms that learn features by embedding nodes or (sub)graphs into a vector space. These tasks come under the broad umbrella of representation learning. A representation learning model learns a mapping function that transforms the graphs' structure information to a low-/high-dimension vector space maintaining all the relevant properties. .
Machine Learning In Complex Networks
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Author : Thiago Christiano Silva
language : en
Publisher: Springer
Release Date : 2016-01-28
Machine Learning In Complex Networks written by Thiago Christiano Silva and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-28 with Computers categories.
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.
Mining Complex Networks
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Author : Bogumil Kaminski
language : en
Publisher: CRC Press
Release Date : 2021-12-14
Mining Complex Networks written by Bogumil Kaminski and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-14 with Mathematics categories.
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.
Complex Networks Their Applications Ix
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Author : Rosa M. Benito
language : en
Publisher: Springer Nature
Release Date : 2020-12-19
Complex Networks Their Applications Ix written by Rosa M. Benito and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-19 with Technology & Engineering categories.
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 IX International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2020). 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 neuroscience networks and technological networks.
Complex Networks Xv
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Author : Federico Botta
language : en
Publisher: Springer Nature
Release Date : 2024-04-13
Complex Networks Xv written by Federico Botta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-13 with Mathematics categories.
The International Conference on Complex Networks (CompleNet) brings together researchers and practitioners from diverse disciplines working on areas related to complex networks. CompleNet has been an active conference since 2009. Over the past two decades, we have witnessed an exponential increase in the number of publications and research centres dedicated to this field of Complex Networks (aka Network Science). From biological systems to computer science, from technical to informational networks, and from economic to social systems, complex networks are becoming pervasive for dozens of applications. It is the interdisciplinary nature of complex networks that CompleNet aims to capture and celebrate. The CompleNet conference is one of the most cherished events by scientists in our field. Maybe it is because of its motivating format, consisting of plenary sessions (no parallel sessions); or perhaps the reason is that it finds the perfect balance between young and senior participation, a balance in the demographics of the presenters, or perhaps it is just the quality of the work presented.
Complex Networks Xiv
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Author : Andreia Sofia Teixeira
language : en
Publisher: Springer Nature
Release Date : 2023-03-29
Complex Networks Xiv written by Andreia Sofia Teixeira and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-29 with Science categories.
This book contains contributions in the area of Network Science, presented at the 14th International Conference on Complex Networks (CompleNet), 24-28 April, 2023 in Aveiro, Portugal. CompleNet is an international conference on complex networks that brings together researchers and practitioners from diverse disciplines—from sociology, biology, physics, and computer science—who share a passion to better understand the interdependencies within and across systems. CompleNet is a venue to discuss ideas and findings about all types networks, from biological, to technological, to informational and social. It is this interdisciplinary nature of complex networks that CompleNet aims to explore and celebrate. The audience of the work are professionals and academics working in Network Science, a highly-multidisciplinary field.
Optimization Learning And Control For Interdependent Complex Networks
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Author : M. Hadi Amini
language : en
Publisher: Springer Nature
Release Date : 2020-02-22
Optimization Learning And Control For Interdependent Complex Networks written by M. Hadi Amini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-22 with Technology & Engineering categories.
This book focuses on a wide range of optimization, learning, and control algorithms for interdependent complex networks and their role in smart cities operation, smart energy systems, and intelligent transportation networks. It paves the way for researchers working on optimization, learning, and control spread over the fields of computer science, operation research, electrical engineering, civil engineering, and system engineering. This book also covers optimization algorithms for large-scale problems from theoretical foundations to real-world applications, learning-based methods to enable intelligence in smart cities, and control techniques to deal with the optimal and robust operation of complex systems. It further introduces novel algorithms for data analytics in large-scale interdependent complex networks. • Specifies the importance of efficient theoretical optimization and learning methods in dealing with emerging problems in the context of interdependent networks • Provides a comprehensive investigation of advance data analytics and machine learning algorithms for large-scale complex networks • Presents basics and mathematical foundations needed to enable efficient decision making and intelligence in interdependent complex networks M. Hadi Amini is an Assistant Professor at the School of Computing and Information Sciences at Florida International University (FIU). He is also the founding director of Sustainability, Optimization, and Learning for InterDependent networks laboratory (solid lab). He received his Ph.D. and M.Sc. from Carnegie Mellon University in 2019 and 2015 respectively. He also holds a doctoral degree in Computer Science and Technology. Prior to that, he received M.Sc. from Tarbiat Modares University in 2013, and the B.Sc. from Sharif University of Technology in 2011.
Complex Networks Xii
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Author : Andreia Sofia Teixeira
language : en
Publisher: Springer Nature
Release Date : 2021-07-29
Complex Networks Xii written by Andreia Sofia Teixeira and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-29 with Science categories.
This book contains contributions presented at the 12th International Conference on Complex Networks (CompleNet), 24-26 May 2021. CompleNet is an international conference on complex networks that brings together researchers and practitioners from diverse disciplines—from sociology, biology, physics, and computer science—who share a passion to better understand the interdependencies within and across systems. CompleNet is a venue to discuss ideas and findings about all types networks, from biological, to technological, to informational and social. It is this interdisciplinary nature of complex networks that CompleNet aims to explore and celebrate.
Complex Networks Their Applications Xiii
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Author : Hocine Cherifi
language : en
Publisher: Springer Nature
Release Date : 2025-05-12
Complex Networks Their Applications Xiii written by Hocine Cherifi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-12 with Science categories.
This book highlights cutting-edge research in 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 XIII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2024). The carefully selected papers cover a wide range of theoretical topics such as network embedding and network geometry; community structure, network dynamics; diffusion, epidemics, and spreading processes; machine learning and graph neural networks, as well as all the main network applications, including social and political networks; networks in finance and economics; biological networks and technological networks.