Robust Representation For Data Analytics

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Robust Representation for Data Analytics

Author : Sheng Li
Publisher : Springer
ISBN 13 : 3319601768
Total Pages : 224 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Robust Representation for Data Analytics by : Sheng Li

Download or read book Robust Representation for Data Analytics written by Sheng Li and published by Springer. This book was released on 2017-08-09 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the concepts and models of robust representation learning, and provides a set of solutions to deal with real-world data analytics tasks, such as clustering, classification, time series modeling, outlier detection, collaborative filtering, community detection, etc. Three types of robust feature representations are developed, which extend the understanding of graph, subspace, and dictionary. Leveraging the theory of low-rank and sparse modeling, the authors develop robust feature representations under various learning paradigms, including unsupervised learning, supervised learning, semi-supervised learning, multi-view learning, transfer learning, and deep learning. Robust Representations for Data Analytics covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.

Proceedings of International Conference on Data Analytics and Insights, ICDAI 2023

Author : Nabendu Chaki
Publisher : Springer Nature
ISBN 13 : 9819938783
Total Pages : 801 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Proceedings of International Conference on Data Analytics and Insights, ICDAI 2023 by : Nabendu Chaki

Download or read book Proceedings of International Conference on Data Analytics and Insights, ICDAI 2023 written by Nabendu Chaki and published by Springer Nature. This book was released on 2023-07-24 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Analytics and Insights (ICDAI 2023), organized by Techno International, Kolkata, India, during May 11–13, 2023. The book covers important topics like sensor and network data analytics and insights; big data analytics and insights; biological and biomedical data analysis and insights; optimization techniques, time series analysis and forecasting; power and energy systems data analytics and insights; civil and environmental data analytics and insights; and industry and applications.

Advances in Big Data Analytics

Author : Yong Shi
Publisher : Springer Nature
ISBN 13 : 9811636079
Total Pages : 733 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Advances in Big Data Analytics by : Yong Shi

Download or read book Advances in Big Data Analytics written by Yong Shi and published by Springer Nature. This book was released on 2022-01-13 with total page 733 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, big data affects countless aspects of our daily lives. This book provides a comprehensive and cutting-edge study on big data analytics, based on the research findings and applications developed by the author and his colleagues in related areas. It addresses the concepts of big data analytics and/or data science, multi-criteria optimization for learning, expert and rule-based data analysis, support vector machines for classification, feature selection, data stream analysis, learning analysis, sentiment analysis, link analysis, and evaluation analysis. The book also explores lessons learned in applying big data to business, engineering and healthcare. Lastly, it addresses the advanced topic of intelligence-quotient (IQ) tests for artificial intelligence. /divSince each aspect mentioned above concerns a specific domain of application, taken together, the algorithms, procedures, analysis and empirical studies presented here offer a general picture of big data developments. Accordingly, the book can not only serve as a textbook for graduates with a fundamental grasp of training in big data analytics, but can also show practitioners how to use the proposed techniques to deal with real-world big data problems.

Feature Engineering for Machine Learning and Data Analytics

Author : Guozhu Dong
Publisher : CRC Press
ISBN 13 : 1351721275
Total Pages : 400 pages
Book Rating : 4.3/5 (517 download)

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Book Synopsis Feature Engineering for Machine Learning and Data Analytics by : Guozhu Dong

Download or read book Feature Engineering for Machine Learning and Data Analytics written by Guozhu Dong and published by CRC Press. This book was released on 2018-03-14 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feature engineering plays a vital role in big data analytics. Machine learning and data mining algorithms cannot work without data. Little can be achieved if there are few features to represent the underlying data objects, and the quality of results of those algorithms largely depends on the quality of the available features. Feature Engineering for Machine Learning and Data Analytics provides a comprehensive introduction to feature engineering, including feature generation, feature extraction, feature transformation, feature selection, and feature analysis and evaluation. The book presents key concepts, methods, examples, and applications, as well as chapters on feature engineering for major data types such as texts, images, sequences, time series, graphs, streaming data, software engineering data, Twitter data, and social media data. It also contains generic feature generation approaches, as well as methods for generating tried-and-tested, hand-crafted, domain-specific features. The first chapter defines the concepts of features and feature engineering, offers an overview of the book, and provides pointers to topics not covered in this book. The next six chapters are devoted to feature engineering, including feature generation for specific data types. The subsequent four chapters cover generic approaches for feature engineering, namely feature selection, feature transformation based feature engineering, deep learning based feature engineering, and pattern based feature generation and engineering. The last three chapters discuss feature engineering for social bot detection, software management, and Twitter-based applications respectively. This book can be used as a reference for data analysts, big data scientists, data preprocessing workers, project managers, project developers, prediction modelers, professors, researchers, graduate students, and upper level undergraduate students. It can also be used as the primary text for courses on feature engineering, or as a supplement for courses on machine learning, data mining, and big data analytics.

Big Data Analytics for Large-Scale Multimedia Search

Author : Stefanos Vrochidis
Publisher : John Wiley & Sons
ISBN 13 : 1119377005
Total Pages : 421 pages
Book Rating : 4.1/5 (193 download)

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Book Synopsis Big Data Analytics for Large-Scale Multimedia Search by : Stefanos Vrochidis

Download or read book Big Data Analytics for Large-Scale Multimedia Search written by Stefanos Vrochidis and published by John Wiley & Sons. This book was released on 2019-03-18 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area of multimedia retrieval and pays close attention to the issue of scalability Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios Includes tables, illustrations, and figures Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.

Enhancing Urban Sustainability with Data, Modeling, and Simulation

Author : National Academies of Sciences, Engineering, and Medicine
Publisher : National Academies Press
ISBN 13 : 0309494141
Total Pages : 109 pages
Book Rating : 4.3/5 (94 download)

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Book Synopsis Enhancing Urban Sustainability with Data, Modeling, and Simulation by : National Academies of Sciences, Engineering, and Medicine

Download or read book Enhancing Urban Sustainability with Data, Modeling, and Simulation written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-09-24 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: On January 30-31, 2019 the Board on Mathematical Sciences and Analytics, in collaboration with the Board on Energy and Environmental Systems and the Computer Science and Telecommunications Board, convened a workshop in Washington, D.C. to explore the frontiers of mathematics and data science needs for sustainable urban communities. The workshop strengthened the emerging interdisciplinary network of practitioners, business leaders, government officials, nonprofit stakeholders, academics, and policy makers using data, modeling, and simulation for urban and community sustainability, and addressed common challenges that the community faces. Presentations highlighted urban sustainability research efforts and programs under way, including research into air quality, water management, waste disposal, and social equity and discussed promising urban sustainability research questions that improved use of big data, modeling, and simulation can help address. This publication summarizes the presentation and discussion of the workshop.

Machine Learning Approach for Cloud Data Analytics in IoT

Author : Sachi Nandan Mohanty
Publisher : John Wiley & Sons
ISBN 13 : 1119785855
Total Pages : 528 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Machine Learning Approach for Cloud Data Analytics in IoT by : Sachi Nandan Mohanty

Download or read book Machine Learning Approach for Cloud Data Analytics in IoT written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2021-07-14 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.

Robust Latent Feature Learning for Incomplete Big Data

Author : Di Wu
Publisher : Springer Nature
ISBN 13 : 981198140X
Total Pages : 119 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Robust Latent Feature Learning for Incomplete Big Data by : Di Wu

Download or read book Robust Latent Feature Learning for Incomplete Big Data written by Di Wu and published by Springer Nature. This book was released on 2022-12-06 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: Incomplete big data are frequently encountered in many industrial applications, such as recommender systems, the Internet of Things, intelligent transportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature analysis (LFA) is one of the most popular representation learning methods tailored for incomplete big data due to its high accuracy, computational efficiency, and ease of scalability. The crux of analyzing incomplete big data lies in addressing the uncertainty problem caused by their incomplete characteristics. However, existing LFA methods do not fully consider such uncertainty. In this book, the author introduces several robust latent feature learning methods to address such uncertainty for effectively and efficiently analyzing incomplete big data, including robust latent feature learning based on smooth L1-norm, improving robustness of latent feature learning using L1-norm, improving robustness of latent feature learning using double-space, data-characteristic-aware latent feature learning, posterior-neighborhood-regularized latent feature learning, and generalized deep latent feature learning. Readers can obtain an overview of the challenges of analyzing incomplete big data and how to employ latent feature learning to build a robust model to analyze incomplete big data. In addition, this book provides several algorithms and real application cases, which can help students, researchers, and professionals easily build their models to analyze incomplete big data.

Big data analytics for smart healthcare applications

Author : Celestine Iwendi
Publisher : Frontiers Media SA
ISBN 13 : 2832515754
Total Pages : 1365 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Big data analytics for smart healthcare applications by : Celestine Iwendi

Download or read book Big data analytics for smart healthcare applications written by Celestine Iwendi and published by Frontiers Media SA. This book was released on 2023-04-17 with total page 1365 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Introduction to Data Science

Author : Rafael A. Irizarry
Publisher : CRC Press
ISBN 13 : 1000708039
Total Pages : 794 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Introduction to Data Science by : Rafael A. Irizarry

Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.

Cognitive Computing and Big Data Analytics

Author : Judith S. Hurwitz
Publisher : John Wiley & Sons
ISBN 13 : 1118896785
Total Pages : 288 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Cognitive Computing and Big Data Analytics by : Judith S. Hurwitz

Download or read book Cognitive Computing and Big Data Analytics written by Judith S. Hurwitz and published by John Wiley & Sons. This book was released on 2015-04-08 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to learning technologies that unlock thevalue in big data Cognitive Computing provides detailed guidance towardbuilding a new class of systems that learn from experience andderive insights to unlock the value of big data. This book helpstechnologists understand cognitive computing's underlyingtechnologies, from knowledge representation techniques and naturallanguage processing algorithms to dynamic learning approaches basedon accumulated evidence, rather than reprogramming. Detailed caseexamples from the financial, healthcare, and manufacturing walkreaders step-by-step through the design and testing of cognitivesystems, and expert perspectives from organizations such asCleveland Clinic, Memorial Sloan-Kettering, as well as commercialvendors that are creating solutions. These organizations provideinsight into the real-world implementation of cognitive computingsystems. The IBM Watson cognitive computing platform is describedin a detailed chapter because of its significance in helping todefine this emerging market. In addition, the book includesimplementations of emerging projects from Qualcomm, Hitachi, Googleand Amazon. Today's cognitive computing solutions build on establishedconcepts from artificial intelligence, natural language processing,ontologies, and leverage advances in big data management andanalytics. They foreshadow an intelligent infrastructure thatenables a new generation of customer and context-aware smartapplications in all industries. Cognitive Computing is a comprehensive guide to thesubject, providing both the theoretical and practical guidancetechnologists need. Discover how cognitive computing evolved from promise toreality Learn the elements that make up a cognitive computingsystem Understand the groundbreaking hardware and softwaretechnologies behind cognitive computing Learn to evaluate your own application portfolio to find thebest candidates for pilot projects Leverage cognitive computing capabilities to transform theorganization Cognitive systems are rightly being hailed as the new era ofcomputing. Learn how these technologies enable emerging firms tocompete with entrenched giants, and forward-thinking establishedfirms to disrupt their industries. Professionals who currently workwith big data and analytics will see how cognitive computing buildson their foundation, and creates new opportunities. CognitiveComputing provides complete guidance to this new level ofhuman-machine interaction.

Robustness Analysis in Decision Aiding, Optimization, and Analytics

Author : Michael Doumpos
Publisher : Springer
ISBN 13 : 3319331213
Total Pages : 321 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Robustness Analysis in Decision Aiding, Optimization, and Analytics by : Michael Doumpos

Download or read book Robustness Analysis in Decision Aiding, Optimization, and Analytics written by Michael Doumpos and published by Springer. This book was released on 2016-07-12 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a broad coverage of the recent advances in robustness analysis in decision aiding, optimization, and analytics. It offers a comprehensive illustration of the challenges that robustness raises in different operations research and management science (OR/MS) contexts and the methodologies proposed from multiple perspectives. Aside from covering recent methodological developments, this volume also features applications of robust techniques in engineering and management, thus illustrating the robustness issues raised in real-world problems and their resolution within advances in OR/MS methodologies. Robustness analysis seeks to address issues by promoting solutions, which are acceptable under a wide set of hypotheses, assumptions and estimates. In OR/MS, robustness has been mostly viewed in the context of optimization under uncertainty. Several scholars, however, have emphasized the multiple facets of robustness analysis in a broader OR/MS perspective that goes beyond the traditional framework, seeking to cover the decision support nature of OR/MS methodologies as well. As new challenges emerge in a “big-data'” era, where the information volume, speed of flow, and complexity increase rapidly, and analytics play a fundamental role for strategic and operational decision-making at a global level, robustness issues such as the ones covered in this book become more relevant than ever for providing sound decision support through more powerful analytic tools.

Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics

Author : Patil, Bhushan
Publisher : IGI Global
ISBN 13 : 1799830543
Total Pages : 583 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics by : Patil, Bhushan

Download or read book Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics written by Patil, Bhushan and published by IGI Global. This book was released on 2020-10-23 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyzing data sets has continued to be an invaluable application for numerous industries. By combining different algorithms, technologies, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our world for the better. The Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics is a collection of innovative research on the methods and applications of data analytics. While highlighting topics including artificial intelligence, data security, and information systems, this book is ideally designed for researchers, data analysts, data scientists, healthcare administrators, executives, managers, engineers, IT consultants, academicians, and students interested in the potential of data application technologies.

Proceedings of Data Analytics and Management

Author : Abhishek Swaroop
Publisher : Springer Nature
ISBN 13 : 9819965470
Total Pages : 666 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Proceedings of Data Analytics and Management by : Abhishek Swaroop

Download or read book Proceedings of Data Analytics and Management written by Abhishek Swaroop and published by Springer Nature. This book was released on 2024-02-06 with total page 666 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes.

Deep Learning-Based Face Analytics

Author : Nalini K Ratha
Publisher : Springer Nature
ISBN 13 : 3030746976
Total Pages : 405 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Deep Learning-Based Face Analytics by : Nalini K Ratha

Download or read book Deep Learning-Based Face Analytics written by Nalini K Ratha and published by Springer Nature. This book was released on 2021-08-16 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recognition, etc. The authors also discuss merits and drawbacks of available approaches and identifies promising avenues of research in this rapidly evolving field. Even though there have been a number of different approaches proposed in the literature for face recognition based on deep learning methods, there is not a single book available in the literature that gives a complete overview of these methods. The proposed book captures the state of the art in face recognition using various deep learning methods, and it covers a variety of different topics related to face recognition. This book is aimed at graduate students studying electrical engineering and/or computer science. Biometrics is a course that is widely offered at both undergraduate and graduate levels at many institutions around the world: This book can be used as a textbook for teaching topics related to face recognition. In addition, the work is beneficial to practitioners in industry who are working on biometrics-related problems. The prerequisites for optimal use are the basic knowledge of pattern recognition, machine learning, probability theory, and linear algebra.

Big Data Analytics

Author : Srinath Srinivasa
Publisher : Springer
ISBN 13 : 3319138200
Total Pages : 197 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Big Data Analytics by : Srinath Srinivasa

Download or read book Big Data Analytics written by Srinath Srinivasa and published by Springer. This book was released on 2014-12-15 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed conference proceedings of the Third International Conference on Big Data Analytics, BDA 2014, held in New Delhi, India, in December 2014. The 11 revised full papers and 6 short papers were carefully reviewed and selected from 35 submissions and cover topics on media analytics; geospatial big data; semantics and data models; search and retrieval; graphics and visualization; application-specific big data.

Knowledge Science, Engineering and Management

Author : Han Qiu
Publisher : Springer Nature
ISBN 13 : 3030821366
Total Pages : 734 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Knowledge Science, Engineering and Management by : Han Qiu

Download or read book Knowledge Science, Engineering and Management written by Han Qiu and published by Springer Nature. This book was released on 2021-08-07 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set constitutes the refereed proceedings of the 14th International Conference on Knowledge Science, Engineering and Management, KSEM 2021, held in Tokyo, Japan, in August 2021. The 164 revised full papers were carefully reviewed and selected from 492 submissions. The contributions are organized in the following topical sections: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management with optimization and security.