Big Data Analytics Methods And Applications
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Big Data Analytics
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Author : Saumyadipta Pyne
language : en
Publisher: Springer
Release Date : 2016-10-12
Big Data Analytics written by Saumyadipta Pyne and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-12 with Computers categories.
This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.
Big Data Analytics Methods And Applications
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Author : Dr.V.Sudharshan
language : en
Publisher: SK Research Group of Companies
Release Date : 2024-10-27
Big Data Analytics Methods And Applications written by Dr.V.Sudharshan and has been published by SK Research Group of Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-27 with Language Arts & Disciplines categories.
Dr.V.Sudharshan, Professor, Department of Computer Science & Engineering, Sri Chaitanaya Institute of Technology and Research (SCIT), Khammam, Telangana, India. Prof.Pannala Krishna Murthy, Professor, Department of Electrical and Electronic Engineering, Jaya Prakash Narayan College of Engineering, Hyderabad, Telangana, India. Mr.A.Mallikarjun, Assistant Professor, Department of Computer Science & Engineering, Sri Chaitanya Institute of Technology and Research (SCIT), Khammam, Telangana, India.
Big Data Analytics
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Author : Erik Steven Paulson
language : en
Publisher:
Release Date : 2018
Big Data Analytics written by Erik Steven Paulson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Big Data is now pervasive. This has driven a critical need to develop novel methods to store and process data at large scale, as well as to develop new applications to use and make sense of this data. This dissertation makes two contributions toward addressing this need. First, we study methods for large-scale data analysis. In particular, we compare the popular MapReduce model to parallel relational database management systems, and empirically analyze their strengths and weaknesses. We evaluate both kinds of systems in terms of performance and development complexity. To this end, we define a collection of benchmarks that we have run on an open-source version of MR as well as on two parallel DBMSs. For each benchmark, we measure each system's performance for various degrees of parallelism on a cluster of 100 shared-nothing nodes. Our results reveal some interesting trade-offs. We speculate about the causes of the dramatic performance difference and consider implementation concepts that future systems should take from both kinds of architectures. In the second contribution, we examine how Big Data scaling methods can be used to build a scalable and flexible cloud-based entity matching applications, and what lessons can be learned for future development of similar applications. Entity matching (EM) finds disparate data instances that refer to the same real-world entity. EM has been long studied and is crucial to many fields, and will become even more so in the age of Big Data. However, it is still very difficult for domain scientists to use EM systems, especially at scale. In response, we have developed CloudMatcher, a cloud/crowd service for EM. CloudMatcher aims to be a fast, easy- to-use, scalable, and highly available EM service on the Web. As far as we can tell, no such application has been developed for EM in the data management research community. We describe CloudMatcher's development and deployment, providing a detailed analysis of its performance over several representative datasets and in several scale-up experiments, and discussing lessons learned. Taken together, our contributions in this dissertation advance the topic of Big Data analytics, for both aspects of methods and 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.
Applications Of Big Data Analytics
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Author : Mohammed M. Alani
language : en
Publisher: Springer
Release Date : 2018-07-23
Applications Of Big Data Analytics written by Mohammed M. Alani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-23 with Computers categories.
This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery. Topics and features: Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicing Explores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plants Describes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenarios Proposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disorders Reviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree vertices Presents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessment This practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects. Dr. Mohammed M. Alani is an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE. Dr. Hissam Tawfik is a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK. Dr. Mohammed Saeed is a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE. Dr. Obinna Anya is a Research Staff Member at IBM Research – Almaden, San Jose, CA, USA.
Data Analytics And Big Data
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Author : Soraya Sedkaoui
language : en
Publisher: John Wiley & Sons
Release Date : 2018-05-24
Data Analytics And Big Data written by Soraya Sedkaoui 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 2018-05-24 with Computers categories.
The main purpose of this book is to investigate, explore and describe approaches and methods to facilitate data understanding through analytics solutions based on its principles, concepts and applications. But analyzing data is also about involving the use of software. For this, and in order to cover some aspect of data analytics, this book uses software (Excel, SPSS, Python, etc) which can help readers to better understand the analytics process in simple terms and supporting useful methods in its application.
Social Big Data Analytics
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Author : Bilal Abu-Salih
language : en
Publisher: Springer Nature
Release Date : 2021-03-10
Social Big Data Analytics written by Bilal Abu-Salih and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-10 with Business & Economics categories.
This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.
Proceedings Of The 2024 4th International Conference On Education Language And Art Icela 2024
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Author : Muhammad Faizal A. Ghani
language : en
Publisher: Springer Nature
Release Date : 2025-03-13
Proceedings Of The 2024 4th International Conference On Education Language And Art Icela 2024 written by Muhammad Faizal A. Ghani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Education categories.
This is an open access book. In today's deepening globalization, education, language and art, as the core components of the human knowledge system, play an immeasurable role in promoting cultural exchanges, improving the quality of education and enriching artistic expression. Although independent of each other, these three fields have interwoven influences, passing on and innovating the values and expressions of language and art through education, while language and art in turn enrich the means and ideas of education. Therefore, it is of great academic and practical significance to explore the intersection of these three aspects to promote the development and integration of various fields.
Big Data Analytics Methods
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Author : Peter Ghavami
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2019-12-16
Big Data Analytics Methods written by Peter Ghavami and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-16 with Business & Economics categories.
Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.
Ict For Intelligent Systems
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Author : Jyoti Choudrie
language : en
Publisher: Springer Nature
Release Date : 2026-01-01
Ict For Intelligent Systems written by Jyoti Choudrie and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-01 with Computers categories.
This book gathers papers addressing state-of-the-art research in all areas of information and communication technologies and their applications in intelligent computing, cloud storage, data mining, and software analysis. It presents the outcomes of the 10th International Conference on Information and Communication Technology for Intelligent Systems (ICTIS 2025), held in New York, USA. The book discusses the fundamentals of various data analysis techniques and algorithms, making it a valuable resource for researchers and practitioners alike.