Principles Of Big Graph In Depth Insight

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Principles Of Big Graph In Depth Insight

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Author : Ripon Patgiri
language : en
Publisher: Elsevier
Release Date : 2023-01-26

Principles Of Big Graph In Depth Insight written by Ripon Patgiri and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-26 with Computers categories.

Big Graph is an engineering research field that is gaining enormous popularity among academicians, industrialists, and practitioners. The Big Graph is applied in research areas such as bioinformatics, social systems administration, computer networking, complex networks, and data streaming. Big Graph technology is also used for biological networks, scholar article citation networks, protein-protein interaction, and semantic networks. Big Graph consists of millions of nodes and trillions of edges growing exponentially; hence, Big Graph needs large computing machinery for processing, which is a grand challenge....(from the Preface)

Principles Of Big Graph In Depth Insight

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Author :
language : en
Publisher: Elsevier
Release Date : 2023-01-24

Principles Of Big Graph In Depth Insight written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-24 with Computers categories.

Principles of Big Graph: In-depth Insight, Volume 128 in the Advances in Computer series, highlights new advances in the field with this new volume presenting interesting chapters on a variety of topics, including CESDAM: Centered subgraph data matrix for large graph representation, Bivariate, cluster and suitability analysis of NoSQL Solutions for big graph applications, An empirical investigation on Big Graph using deep learning, Analyzing correlation between quality and accuracy of graph clustering, geneBF: Filtering protein-coded gene graph data using bloom filter, Processing large graphs with an alternative representation, MapReduce based convolutional graph neural networks: A comprehensive review. Fast exact triangle counting in large graphs using SIMD acceleration, A comprehensive investigation on attack graphs, Qubit representation of a binary tree and its operations in quantum computation, Modified ML-KNN: Role of similarity measures and nearest neighbor configuration in multi label text classification on big social network graph data, Big graph based online learning through social networks, Community detection in large-scale real-world networks, Power rank: An interactive web page ranking algorithm, GA based energy efficient modelling of a wireless sensor network, The major challenges of big graph and their solutions: A review, and An investigation on socio-cyber crime graph. - Provides an update on the issues and challenges faced by current researchers - Updates on future research agendas - Includes advanced topics for intensive research for researchers

Modeling Simulation And Optimization

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Author : Biplab Das
language : en
Publisher: Springer Nature
Release Date : 2022-06-28

Modeling Simulation And Optimization written by Biplab Das and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-28 with Technology & Engineering categories.

This book includes selected peer-reviewed papers presented at the International Conference on Modeling, Simulation and Optimization (CoMSO 2021), organized by National Institute of Technology, Silchar, Assam, India, during December 16–18, 2021. The book covers topics of modeling, simulation and optimization, including computational modeling and simulation, system modeling and simulation, device/VLSI modeling and simulation, control theory and applications, modeling and simulation of energy systems and optimization. The book disseminates various models of diverse systems and includes solutions of emerging challenges of diverse scientific fields.

Advances In Smart Energy Systems

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Author : Biplab Das
language : en
Publisher: Springer Nature
Release Date : 2022-08-31

Advances In Smart Energy Systems written by Biplab Das and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-31 with Technology & Engineering categories.

This book discusses smart computing techniques which offer an effective solution for investigating and modeling the stochastic behavior of renewable energy generation, operation of grid-connected renewable energy systems, and smart decision-making among alternatives. It also discusses applications of soft computing techniques to make an intelligent decision for optimum use of suitable alternatives which gives an upper hand compared to conventional systems. It includes upgradation of the existing system by embedding of machine intelligence. The authors present combination of use of neutral networks, fuzzy systems, and genetic algorithms which are illustrated in several applications including forecasting, security, verification, diagnostics of a specific fault, efficiency optimization, etc. Smart energy systems integrate a holistic approach in diverse sectors including electricity, thermal comfort, power industry, transportation. It allows affordable and sustainable solutions to solve the future energy demands with suitable alternatives. Thus, contributions regarding integration of the machine intelligence with the energy system, for efficient collection and effective utilization of the available energy sources, are useful for further advanced studies.

Modern Artificial Intelligence And Data Science 2024

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Author : Abdellah Idrissi
language : en
Publisher: Springer Nature
Release Date : 2024-10-03

Modern Artificial Intelligence And Data Science 2024 written by Abdellah Idrissi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-03 with Computers categories.

This book, through its various chapters presenting recent advances in Modern Artificial Intelligence and Data Science as well as their applications, aims to set up lasting and real applications necessary for both academics and professionals. By its proposals of new ideas, it serves as a real guide both to informed readers and to beginners in these specialized fields. It also covers applications that discuss how they can support societal challenges such as education, health, agriculture, clean energy, business, environment, and security. Readers will find here the fruit of many research ideas covering a wide range of application areas that can be explored for the advancement of their research or the development of their business. These ideas present new techniques and trends projected in various areas of daily life. This book is therefore intended for Designers, Developers, Decision-Makers, Consultants, Engineers, and of course Master's/Doctorate Students, Researchers, and Universities.

Graph Representation Learning

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Author : William L. Hamilton
language : en
Publisher: Springer Nature
Release Date : 2022-06-01

Graph Representation Learning written by William L. Hamilton and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.

Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.

Data Analytics

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Author : Mohiuddin Ahmed
language : en
Publisher: CRC Press
Release Date : 2018-09-21

Data Analytics written by Mohiuddin Ahmed and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-21 with Computers categories.

Large data sets arriving at every increasing speeds require a new set of efficient data analysis techniques. Data analytics are becoming an essential component for every organization and technologies such as health care, financial trading, Internet of Things, Smart Cities or Cyber Physical Systems. However, these diverse application domains give rise to new research challenges. In this context, the book provides a broad picture on the concepts, techniques, applications, and open research directions in this area. In addition, it serves as a single source of reference for acquiring the knowledge on emerging Big Data Analytics technologies.

Data Analytics On Graphs

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Author : Ljubisa Stankovic
language : en
Publisher:
Release Date : 2020-12-22

Data Analytics On Graphs written by Ljubisa Stankovic and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-22 with Data mining categories.

Aimed at readers with a good grasp of the fundamentals of data analytics, this book sets out the fundamentals of graph theory and the emerging mathematical techniques for the analysis of a wide range of data acquired on graph environments. This book will be a useful friend and a helpful companion to all involved in data gathering and analysis.

Principles Of Database Management

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Author : Wilfried Lemahieu
language : en
Publisher: Cambridge University Press
Release Date : 2018-07-12

Principles Of Database Management written by Wilfried Lemahieu and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-12 with Computers categories.

Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.

Graph Analysis And Visualization

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Author : Richard Brath
language : en
Publisher: John Wiley & Sons
Release Date : 2015-01-27

Graph Analysis And Visualization written by Richard Brath and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-27 with Computers categories.

Wring more out of the data with a scientific approach to analysis Graph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations using a rich and engaging set of examples from sports, finance, marketing, security, social media, and more. You will find practical guidance toward pattern identification and using various data sources, including Big Data, plus clear instruction on the use of software and programming. The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book. Science has already reaped the benefit of network and graph theory, which has powered breakthroughs in physics, economics, genetics, and more. This book brings those proven techniques into the world of business, finance, strategy, and design, helping extract more information from data and better communicate the results to decision-makers. Study graphical examples of networks using clear and insightful visualizations Analyze specifically-curated, easy-to-use data sets from various industries Learn the software tools and programming languages that extract insights from data Code examples using the popular Python programming language There is a tremendous body of scientific work on network and graph theory, but very little of it directly applies to analyst functions outside of the core sciences – until now. Written for those seeking empirically based, systematic analysis methods and powerful tools that apply outside the lab, Graph Analysis and Visualization is a thorough, authoritative resource.