Noise Filtering For Big Data Analytics

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Noise Filtering for Big Data Analytics

Author : Souvik Bhattacharyya
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110697262
Total Pages : 195 pages
Book Rating : 4.1/5 (16 download)

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Book Synopsis Noise Filtering for Big Data Analytics by : Souvik Bhattacharyya

Download or read book Noise Filtering for Big Data Analytics written by Souvik Bhattacharyya and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-06-21 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model. Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information. This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.

Big Data Preprocessing

Author : Julián Luengo
Publisher : Springer Nature
ISBN 13 : 3030391051
Total Pages : 193 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Big Data Preprocessing by : Julián Luengo

Download or read book Big Data Preprocessing written by Julián Luengo and published by Springer Nature. This book was released on 2020-03-16 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensible overview of Big Data Preprocessing, which includes a formal description of each problem. It also focuses on the most relevant proposed solutions. This book illustrates actual implementations of algorithms that helps the reader deal with these problems. This book stresses the gap that exists between big, raw data and the requirements of quality data that businesses are demanding. This is called Smart Data, and to achieve Smart Data the preprocessing is a key step, where the imperfections, integration tasks and other processes are carried out to eliminate superfluous information. The authors present the concept of Smart Data through data preprocessing in Big Data scenarios and connect it with the emerging paradigms of IoT and edge computing, where the end points generate Smart Data without completely relying on the cloud. Finally, this book provides some novel areas of study that are gathering a deeper attention on the Big Data preprocessing. Specifically, it considers the relation with Deep Learning (as of a technique that also relies in large volumes of data), the difficulty of finding the appropriate selection and concatenation of preprocessing techniques applied and some other open problems. Practitioners and data scientists who work in this field, and want to introduce themselves to preprocessing in large data volume scenarios will want to purchase this book. Researchers that work in this field, who want to know which algorithms are currently implemented to help their investigations, may also be interested in this book.

Noise Filtering for Big Data Analytics

Author : Souvik Bhattacharyya
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110697211
Total Pages : 164 pages
Book Rating : 4.1/5 (16 download)

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Book Synopsis Noise Filtering for Big Data Analytics by : Souvik Bhattacharyya

Download or read book Noise Filtering for Big Data Analytics written by Souvik Bhattacharyya and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-06-21 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model. Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information. This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.

Big Data Analytics Methods

Author : Peter Ghavami
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 1547401583
Total Pages : 290 pages
Book Rating : 4.5/5 (474 download)

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Book Synopsis Big Data Analytics Methods by : Peter Ghavami

Download or read book Big Data Analytics Methods written by Peter Ghavami and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-12-16 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Research Practitioner's Handbook on Big Data Analytics

Author : S. Sasikala
Publisher : CRC Press
ISBN 13 : 1000578364
Total Pages : 310 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Research Practitioner's Handbook on Big Data Analytics by : S. Sasikala

Download or read book Research Practitioner's Handbook on Big Data Analytics written by S. Sasikala and published by CRC Press. This book was released on 2023-05-04 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume addresses the growing interest in and use of big data analytics in many industries and in many research fields around the globe; it is a comprehensive resource on the core concepts of big data analytics and the tools, techniques, and methodologies. The book gives the why and the how of big data analytics in an organized and straightforward manner, using both theoretical and practical approaches. The book’s authors have organized the contents in a systematic manner, starting with an introduction and overview of big data analytics and then delving into pre-processing methods, feature selection methods and algorithms, big data streams, and big data classification. Such terms and methods as swarm intelligence, data mining, the bat algorithm and genetic algorithms, big data streams, and many more are discussed. The authors explain how deep learning and machine learning along with other methods and tools are applied in big data analytics. The last section of the book presents a selection of illustrative case studies that show examples of the use of data analytics in industries such as health care, business, education, and social media.

Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges

Author : Aboul Ella Hassanien
Publisher : Springer Nature
ISBN 13 : 303059338X
Total Pages : 648 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges by : Aboul Ella Hassanien

Download or read book Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2020-12-14 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Big Data Analytics Methods

Author : Peter Ghavami
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 1547401567
Total Pages : 254 pages
Book Rating : 4.5/5 (474 download)

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Book Synopsis Big Data Analytics Methods by : Peter Ghavami

Download or read book Big Data Analytics Methods written by Peter Ghavami and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-12-16 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Software Project Management

Author : Moh’d A. Radaideh
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3111206866
Total Pages : 536 pages
Book Rating : 4.1/5 (112 download)

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Book Synopsis Software Project Management by : Moh’d A. Radaideh

Download or read book Software Project Management written by Moh’d A. Radaideh and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-12-18 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software Project Management (SPM) differs from the Traditional Project Management (PM) approaches in that Software Engineering requires multiple rounds of Software Testing, and Updating in accordance with their Testing results and their customer’s feedback. Thus, SPM introduces unique life cycle processes.This book presents an introduction and a critical analysis of the main Software Project Management Frameworks, and offers the author’s original approach to SPM as developed by him over years of professional and teaching experience in the Academia and the IT/Software Industry. It also provides Executive Summaries of the Project Management and Software Project Management Perspectives offered by the Project Management Institute (PMI), the IEEE-Computer Society (IEEE-CS), and the SCRUM Project Management Bodies such as the SCRUMstudy.

Big Data Analytics for Cyber-Physical System in Smart City

Author : Mohammed Atiquzzaman
Publisher : Springer Nature
ISBN 13 : 9811525684
Total Pages : 2049 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Big Data Analytics for Cyber-Physical System in Smart City by : Mohammed Atiquzzaman

Download or read book Big Data Analytics for Cyber-Physical System in Smart City written by Mohammed Atiquzzaman and published by Springer Nature. This book was released on 2020-01-11 with total page 2049 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers a selection of peer-reviewed papers presented at the first Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2019) conference, held in Shengyang, China, on 28–29 December 2019. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John Macintyre
Publisher : Springer Nature
ISBN 13 : 3030895114
Total Pages : 999 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by : John Macintyre

Download or read book The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy written by John Macintyre and published by Springer Nature. This book was released on 2021-11-02 with total page 999 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Big Data Analytics Techniques for Market Intelligence

Author : Darwish, Dina
Publisher : IGI Global
ISBN 13 :
Total Pages : 536 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Big Data Analytics Techniques for Market Intelligence by : Darwish, Dina

Download or read book Big Data Analytics Techniques for Market Intelligence written by Darwish, Dina and published by IGI Global. This book was released on 2024-01-04 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ever-expanding realm of Big Data poses a formidable challenge for academic scholars and professionals due to the sheer magnitude and diversity of data types, along with the continuous influx of information from various sources. Extracting valuable insights from this vast and complex dataset is crucial for organizations to uncover market intelligence and make informed decisions. However, without the proper guidance and understanding of Big Data analytics techniques and methodologies, scholars may struggle to navigate this landscape and maximize the potential benefits of their research. In response to this pressing need, Professor Dina Darwish presents Big Data Analytics Techniques for Market Intelligence, a groundbreaking book that addresses the specific challenges faced by scholars and professionals in the field. Through a comprehensive exploration of various techniques and methodologies, this book offers a solution to the hurdles encountered in extracting meaningful information from Big Data. Covering the entire lifecycle of Big Data analytics, including preprocessing, analysis, visualization, and utilization of results, the book equips readers with the knowledge and tools necessary to unlock the power of Big Data and generate valuable market intelligence. With real-world case studies and a focus on practical guidance, scholars and professionals can effectively leverage Big Data analytics to drive strategic decision-making and stay at the forefront of this rapidly evolving field.

Big-Data-Analytics in Astronomy, Science, and Engineering

Author : Shelly Sachdeva
Publisher : Springer Nature
ISBN 13 : 3030966003
Total Pages : 283 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Big-Data-Analytics in Astronomy, Science, and Engineering by : Shelly Sachdeva

Download or read book Big-Data-Analytics in Astronomy, Science, and Engineering written by Shelly Sachdeva and published by Springer Nature. This book was released on 2022-02-17 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 9th International Conference on Big Data Analytics, BDA 2021, which took place virtually during December 7–9, 2021. The 15 full papers and 1 short paper included in this volume were carefully reviewed and selected from 60 submissions. They were organized in topical sections as follows: Data science: systems; data science: architectures; big data analytics in healthcare support systems, information interchange of web data resources; and business analytics.

The Internet of Things and Big Data Analytics

Author : Pethuru Raj
Publisher : CRC Press
ISBN 13 : 1000057399
Total Pages : 341 pages
Book Rating : 4.0/5 ( download)

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Book Synopsis The Internet of Things and Big Data Analytics by : Pethuru Raj

Download or read book The Internet of Things and Big Data Analytics written by Pethuru Raj and published by CRC Press. This book was released on 2020-06-07 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively conveys the theoretical and practical aspects of IoT and big data analytics with the solid contributions from practitioners as well as academicians. This book examines and expounds the unique capabilities of the big data analytics platforms in capturing, cleansing and crunching IoT device/sensor data in order to extricate actionable insights. A number of experimental case studies and real-world scenarios are incorporated in this book in order to instigate our book readers. This book Analyzes current research and development in the domains of IoT and big data analytics Gives an overview of latest trends and transitions happening in the IoT data analytics space Illustrates the various platforms, processes, patterns, and practices for simplifying and streamlining IoT data analytics The Internet of Things and Big Data Analytics: Integrated Platforms and Industry Use Cases examines and accentuates how the multiple challenges at the cusp of IoT and big data can be fully met. The device ecosystem is growing steadily. It is forecast that there will be billions of connected devices in the years to come. When these IoT devices, resource-constrained as well as resource-intensive, interact with one another locally and remotely, the amount of multi-structured data generated, collected, and stored is bound to grow exponentially. Another prominent trend is the integration of IoT devices with cloud-based applications, services, infrastructures, middleware solutions, and databases. This book examines the pioneering technologies and tools emerging and evolving in order to collect, pre-process, store, process and analyze data heaps in order to disentangle actionable insights.

Encyclopedia of Data Science and Machine Learning

Author : Wang, John
Publisher : IGI Global
ISBN 13 : 1799892212
Total Pages : 3296 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Encyclopedia of Data Science and Machine Learning by : Wang, John

Download or read book Encyclopedia of Data Science and Machine Learning written by Wang, John and published by IGI Global. This book was released on 2023-01-20 with total page 3296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.

Intensional First-Order Logic

Author : Zoran Majkic
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110981432
Total Pages : 542 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Intensional First-Order Logic by : Zoran Majkic

Download or read book Intensional First-Order Logic written by Zoran Majkic and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-09-05 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the properties of conservative extensions of First Order Logic (FOL) to new Intensional First Order Logic (IFOL). This extension allows for intensional semantics to be used for concepts, thus affording new and more intelligent IT systems. Insofar as it is conservative, it preserves software applications and constitutes a fundamental advance relative to the current RDB databases, Big Data with NewSQL, Constraint databases, P2P systems and Semantic Web applications. Moreover, the many-valued version of IFOL can support the AI applications based on many-valued logics.

Artificial Intelligence for Fashion Industry in the Big Data Era

Author : Sébastien Thomassey
Publisher : Springer
ISBN 13 : 9811300801
Total Pages : 289 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Artificial Intelligence for Fashion Industry in the Big Data Era by : Sébastien Thomassey

Download or read book Artificial Intelligence for Fashion Industry in the Big Data Era written by Sébastien Thomassey and published by Springer. This book was released on 2018-05-16 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of current issues and challenges in the fashion industry and an update on data-driven artificial intelligence (AI) techniques and their potential implementation in response to those challenges. Each chapter starts off with an example of a data-driven AI technique on a particular sector of the fashion industry (design, manufacturing, supply or retailing), before moving on to illustrate its implementation in a real-world application

Big Data Analytics for Human-Computer Interactions: A New Era of Computation

Author : Kuldeep Singh Kaswan
Publisher : Bentham Science Publishers
ISBN 13 : 9815079948
Total Pages : 392 pages
Book Rating : 4.8/5 (15 download)

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Book Synopsis Big Data Analytics for Human-Computer Interactions: A New Era of Computation by : Kuldeep Singh Kaswan

Download or read book Big Data Analytics for Human-Computer Interactions: A New Era of Computation written by Kuldeep Singh Kaswan and published by Bentham Science Publishers. This book was released on 2023-08-28 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data is playing a vital role in HCI projects across a range of industries: healthcare, cybersecurity, forensics, education, business organizations, and scientific research. Big data analytics requires advanced tools and techniques to store, process and analyze the huge volume of data. Working on HCI projects requires specific skill sets to implement IT solutions. Big Data Analytics for Human-Computer Interactions: A New Era of Computation is a comprehensive guide that discusses the evolution of Big Data in Human Computer Interaction from promise to reality. This book provides an introduction to Big Data and HCI, followed by an overview of the state-of-the-art algorithms for processing big data, Subsequent chapters also explain the characteristics, applications, opportunities and challenges of big data systems, by describing theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in designing HIC systems. The book also presents solutions for analyzing complex patterns in user data and improving productivity. Readers will be able to understand the technology that drives big data solutions in HCI projects and understand its capacity in transforming an organization. The book also helps the reader to understand HCI system design and explains how to evaluate an application portfolio that can be used when selecting pilot projects. This book is a resource for researchers, students, and professionals interested in the fields of HCI, artificial intelligence, data analytics, and computer engineering.