Data Mining And Big Data

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Data Mining And Big Data
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Author : Ying Tan
language : en
Publisher: Springer
Release Date : 2019-07-25
Data Mining And Big Data written by Ying Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-25 with Computers categories.
This book constitutes the refereed proceedings of the 4th International Conference on Data Mining and Big Data, DMBD 2019, held in Chiang Mai, Thailand, in July 2019. The 26 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 79 submissions. They are organized in topical sections named: data analysis; prediction; clustering; classification; mining pattern; mining tasks.
Predictive Analytics Data Mining And Big Data
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Author : S. Finlay
language : en
Publisher: Springer
Release Date : 2014-07-01
Predictive Analytics Data Mining And Big Data written by S. Finlay and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-01 with Business & Economics categories.
This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.
Big Data Data Mining And Machine Learning
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Author : Jared Dean
language : en
Publisher: John Wiley & Sons
Release Date : 2014-05-07
Big Data Data Mining And Machine Learning written by Jared Dean 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 2014-05-07 with Computers categories.
With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.
Big Data Mining And Complexity
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Author : Brian C. Castellani
language : en
Publisher: SAGE
Release Date : 2022-03
Big Data Mining And Complexity written by Brian C. Castellani and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03 with Reference categories.
This book offers a much needed critical introduction to data mining and ‘big data’. Supported by multiple case studies and examples, the authors provide everything needed to explore, evaluate and review big data concepts and techniques.
Data Mining Approaches For Big Data And Sentiment Analysis In Social Media
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Author : Brij Gupta
language : en
Publisher:
Release Date : 2021
Data Mining Approaches For Big Data And Sentiment Analysis In Social Media written by Brij Gupta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Big data categories.
"This book explores the key concepts of data mining and utilizing them on online social media platforms, offering valuable insight into data mining approaches for big data and sentiment analysis in online social media and covering many important security and other aspects and current trends"--
Innovations In Big Data Mining And Embedded Knowledge
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Author : Anna Esposito
language : en
Publisher: Springer
Release Date : 2019-07-03
Innovations In Big Data Mining And Embedded Knowledge written by Anna Esposito and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-03 with Computers categories.
This book addresses the usefulness of knowledge discovery through data mining. With this aim, contributors from different fields propose concrete problems and applications showing how data mining and discovering embedded knowledge from raw data can be beneficial to social organizations, domestic spheres, and ICT markets. Data mining or knowledge discovery in databases (KDD) has received increasing interest due to its focus on transforming large amounts of data into novel, valid, useful, and structured knowledge by detecting concealed patterns and relationships. The concept of knowledge is broad and speculative and has promoted epistemological debates in western philosophies. The intensified interest in knowledge management and data mining stems from the difficulty in identifying computational models able to approximate human behaviors and abilities in resolving organizational, social, and physical problems. Current ICT interfaces are not yet adequately advanced to support and simulate the abilities of physicians, teachers, assistants or housekeepers in domestic spheres. And unlike in industrial contexts where abilities are routinely applied, the domestic world is continuously changing and unpredictable. There are challenging questions in this field: Can knowledge locked in conventions, rules of conduct, common sense, ethics, emotions, laws, cultures, and experiences be mined from data? Is it acceptable for automatic systems displaying emotional behaviors to govern complex interactions based solely on the mining of large volumes of data? Discussing multidisciplinary themes, the book proposes computational models able to approximate, to a certain degree, human behaviors and abilities in resolving organizational, social, and physical problems. The innovations presented are of primary importance for: a. The academic research community b. The ICT market c. Ph.D. students and early stage researchers d. Schools, hospitals, rehabilitation and assisted-living centers e. Representatives from multimedia industries and standardization bodies
Social Big Data Mining
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Author : Hiroshi Ishikawa
language : en
Publisher: CRC Press
Release Date : 2015-03-25
Social Big Data Mining written by Hiroshi Ishikawa and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-25 with Computers categories.
This book focuses on the basic concepts and the related technologies of data mining for social medial. Topics include: big data and social data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language processing, social big data applications, and scalability. It explains
Transparent Data Mining For Big And Small Data
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Author : Tania Cerquitelli
language : en
Publisher: Springer
Release Date : 2017-05-09
Transparent Data Mining For Big And Small Data written by Tania Cerquitelli and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-09 with Computers categories.
This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions. Transparent data mining solutions with desirable properties (e.g. effective, fully automatic, scalable) are covered in the book. Experimental findings of transparent solutions are tailored to different domain experts, and experimental metrics for evaluating algorithmic transparency are presented. The book also discusses societal effects of black box vs. transparent approaches to data mining, as well as real-world use cases for these approaches.As algorithms increasingly support different aspects of modern life, a greater level of transparency is sorely needed, not least because discrimination and biases have to be avoided. With contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical use.
Big Data Mining For Climate Change
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Author : Zhihua Zhang
language : en
Publisher: Elsevier
Release Date : 2019-11-20
Big Data Mining For Climate Change written by Zhihua Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-20 with Science categories.
Climate change mechanisms, impacts, risks, mitigation, adaption, and governance are widely recognized as the biggest, most interconnected problem facing humanity. Big Data Mining for Climate Change addresses one of the fundamental issues facing scientists of climate or the environment: how to manage the vast amount of information available and analyse it. The resulting integrated and interdisciplinary big data mining approaches are emerging, partially with the help of the United Nation's big data climate challenge, some of which are recommended widely as new approaches for climate change research. Big Data Mining for Climate Change delivers a rich understanding of climate-related big data techniques and highlights how to navigate huge amount of climate data and resources available using big data applications. It guides future directions and will boom big-data-driven researches on modeling, diagnosing and predicting climate change and mitigating related impacts. This book mainly focuses on climate network models, deep learning techniques for climate dynamics, automated feature extraction of climate variability, and sparsification of big climate data. It also includes a revelatory exploration of big-data-driven low-carbon economy and management. Its content provides cutting-edge knowledge for scientists and advanced students studying climate change from various disciplines, including atmospheric, oceanic and environmental sciences; geography, ecology, energy, economics, management, engineering, and public policy.
Machine Learning And Big Data Analytics Paradigms Analysis Applications And Challenges
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Author : Aboul Ella Hassanien
language : en
Publisher: Springer Nature
Release Date : 2020-12-14
Machine Learning And Big Data Analytics Paradigms Analysis Applications And Challenges written by Aboul Ella Hassanien and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-14 with Computers categories.
This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.