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Big Data And Social Computing


Big Data And Social Computing
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Big Data And Social Computing


Big Data And Social Computing
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Author : Xiaofeng Meng
language : en
Publisher: Springer Nature
Release Date : 2024-08-01

Big Data And Social Computing written by Xiaofeng Meng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-01 with Computers categories.


This book constitutes the refereed proceedings of the 9th China National Conference on Big Data and Social Computing, BDSC 2024, held in Harbin, China, during August 8–10, 2024. The 28 full papers presented in this volume were carefully reviewed and selected from a total of 141 submissions. The papers in the volume are organized according to the following topics: digital society and public security; modelling and simulation of social systems; internet intelligent algorithm governance; social network and group behavior; innovation, risks, and network security of large language models; and artificial intelligence and cognitive science.



Big Data And Social Science


Big Data And Social Science
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Author : Ian Foster
language : en
Publisher: CRC Press
Release Date : 2016-08-10

Big Data And Social Science written by Ian Foster and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-10 with Mathematics categories.


Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.



Big Data Technologies And Applications


Big Data Technologies And Applications
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Author : Borko Furht
language : en
Publisher: Springer
Release Date : 2016-09-16

Big Data Technologies And Applications written by Borko Furht and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-16 with Computers categories.


The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.



High Performance Big Data Computing


High Performance Big Data Computing
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Author : Dhabaleswar K. Panda
language : en
Publisher:
Release Date : 2022

High Performance Big Data Computing written by Dhabaleswar K. Panda and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Big data categories.


"This book explores how to achieve high performance and scalability for big data middleware and applications"--



Big Data Analytics Systems Algorithms Applications


Big Data Analytics Systems Algorithms Applications
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Author : C.S.R. Prabhu
language : en
Publisher: Springer Nature
Release Date : 2019-10-14

Big Data Analytics Systems Algorithms Applications written by C.S.R. Prabhu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-14 with Computers categories.


This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.



Social Computing With Artificial Intelligence


Social Computing With Artificial Intelligence
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Author : Xun Liang
language : en
Publisher: Springer Nature
Release Date : 2020-09-16

Social Computing With Artificial Intelligence written by Xun Liang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-16 with Computers categories.


This book provides a comprehensive introduction to the application of artificial intelligence in social computing, from fundamental data processing to advanced social network computing. To broaden readers’ understanding of the topics addressed, it includes extensive data and a large number of charts and references, covering theories, techniques and applications. It particularly focuses on data collection, data mining, artificial intelligence algorithms in social computing, and several key applications of social computing application, and also discusses network propagation mechanisms and dynamic analysis, which provide useful insights into how information is disseminated in online social networks. This book is intended for readers with a basic knowledge of advanced mathematics and computer science.



Advanced Data Mining Tools And Methods For Social Computing


Advanced Data Mining Tools And Methods For Social Computing
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Author : Sourav De
language : en
Publisher: Academic Press
Release Date : 2022-01-14

Advanced Data Mining Tools And Methods For Social Computing written by Sourav De and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-14 with Computers categories.


Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis. - Provides insights into the latest research trends in social network analysis - Covers a broad range of data mining tools and methods for social computing and analysis - Includes practical examples and case studies across a range of tools and methods - Features coding examples and supplementary data sets in every chapter



Social Computing


Social Computing
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Author : Wanxiang Che
language : en
Publisher: Springer
Release Date : 2016-07-30

Social Computing written by Wanxiang Che and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-30 with Computers categories.


This two volume set (CCIS 623 and 634) constitutes the refereed proceedings of the Second International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, held in Harbin, China, in August 2016. The 91 revised full papers presented were carefully reviewed and selected from 338 submissions. The papers are organized in topical sections on Research Track (Part I) and Education Track, Industry Track, and Demo Track (Part II) and cover a wide range of topics related to social computing, social media, social network analysis, social modeling, social recommendation, machine learning, data mining.



Computer Supported Cooperative Work And Social Computing


Computer Supported Cooperative Work And Social Computing
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Author : Yuqing Sun
language : en
Publisher: Springer Nature
Release Date : 2021-05-06

Computer Supported Cooperative Work And Social Computing written by Yuqing Sun and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-06 with Computers categories.


This book constitutes the refereed post-conference proceedings of the 15th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2020, held in Shenzhen, China, in November 2020. The 40 revised full papers and 15 revised short papers were carefully reviewed and selected from 137 submissions. The papers of this volume are organized in topical sections on: crowdsourcing, crowd intelligence, and crowd cooperative computing; domain-specific collaborative applications; collaborative mechanisms, models, approaches, algorithms, and systems; social media and online communities; and short papers.



Big Data In Education


Big Data In Education
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Author : Ben Williamson
language : en
Publisher: SAGE
Release Date : 2017-07-24

Big Data In Education written by Ben Williamson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-24 with Education categories.


Big data has the power to transform education and educational research. Governments, researchers and commercial companies are only beginning to understand the potential that big data offers in informing policy ideas, contributing to the development of new educational tools and innovative ways of conducting research. This cutting-edge overview explores the current state-of-play, looking at big data and the related topic of computer code to examine the implications for education and schooling for today and the near future. Key topics include: · The role of learning analytics and educational data science in schools · A critical appreciation of code, algorithms and infrastructures · The rise of ‘cognitive classrooms’, and the practical application of computational algorithms to learning environments · Important digital research methods issues for researchers This is essential reading for anyone studying or working in today′s education environment!