Big Data and Visual Analytics, Sang C. Suh; Thomas Anthony
Автор: Hsu, Hui-Huang Название: Big Data Analytics for Sensor-Network Collected Intelligence ISBN: 0128093935 ISBN-13(EAN): 9780128093931 Издательство: Elsevier Science Рейтинг: Цена: 15159.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services.
It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality.
In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation.
Indexing: The books of this series are submitted to EI-Compendex and SCOPUS
Contains contributions from noted scholars in computer science and electrical engineering from around the globe
Provides a broad overview of recent developments in sensor collected intelligence
Edited by a team comprised of leading thinkers in big data analytics
This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments.
Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people's imaginations as to what a fully connected world can offer.
Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions.
The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.
Автор: Wolfgang Karl H?rdle; Henry Horng-Shing Lu; Xiaoto Название: Handbook of Big Data Analytics ISBN: 3319182838 ISBN-13(EAN): 9783319182834 Издательство: Springer Рейтинг: Цена: 39130.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.
Автор: Sanjay Madria; Takahiro Hara Название: Big Data Analytics and Knowledge Discovery ISBN: 3319227289 ISBN-13(EAN): 9783319227283 Издательство: Springer Рейтинг: Цена: 7826.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 17th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, September 2015. The 31 revised full papers presented were carefully reviewed and selected from 90 submissions. data warehouses; applications of big data analysis;
Автор: Boris Deliba?i?; Jorge E. Hern?ndez; Jason Papatha Название: Decision Support Systems V – Big Data Analytics for Decision Making ISBN: 3319185322 ISBN-13(EAN): 9783319185323 Издательство: Springer Рейтинг: Цена: 5590.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 'Big Data' Decision Making Use Cases.- The Roles of Big Data in the Decision-Support Process: An Empirical Investigation.- Cloud Enabled Big Data Business Platform for Logistics Services: A Research and Development Agenda.- Making Sense of Governmental Activities Over Social Media: A Data-Driven Approach.- Data-Mining and Expert Models for Predicting Injury Risk in Ski Resorts.- The Effects of Performance Ratios in Predicting Corporate Bankruptcy: The Italian Case.- A Tangible Collaborative Decision Support System for Various Variants of the Vehicle Routing Problem.- Decision Support Model for Participatory Management of Water Resource.- Modeling Interactions Among Criteria in MCDM Methods: A Review.
Автор: Wong Название: Big Data Analytics in Genomics ISBN: 3319412787 ISBN-13(EAN): 9783319412788 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace. To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field.
This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA. In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science. Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic.
Автор: Corea Название: Big Data Analytics: A Management Perspective ISBN: 3319389912 ISBN-13(EAN): 9783319389912 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership – while others concern more specific business situations (e.g., initial public offering, growth strategies, etc.). The important matter of selecting the right skills and people for an effective team will be extensively explained, and practical ways to recognize them and understanding their personalities will be provided. Finally, few relevant technological future trends will be acknowledged (i.e., IoT, Artificial intelligence, blockchain, etc.), especially for their close relation with the increasing amount of data and our ability to analyse them faster and more effectively.
Название: Visual Analytics of Movement ISBN: 3642375820 ISBN-13(EAN): 9783642375828 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces a general conceptual framework for the analysis of movement data from various sources. It illustrates all algorithms and methods with the help of sample applications from various domains.
Автор: Ladjel Bellatreche; Sharma Chakravarthy Название: Big Data Analytics and Knowledge Discovery ISBN: 3319642820 ISBN-13(EAN): 9783319642826 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 19th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2017, held in Lyon, France, in August 2017. The 24 revised full papers and 11 short papers presented were carefully reviewed and selected from 97 submissions.
Автор: S. Finlay Название: Predictive Analytics, Data Mining and Big Data ISBN: 1349478687 ISBN-13(EAN): 9781349478682 Издательство: Springer Рейтинг: Цена: 4890.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Naveen Kumar; Vasudha Bhatnagar Название: Big Data Analytics ISBN: 3319270567 ISBN-13(EAN): 9783319270562 Издательство: Springer Рейтинг: Цена: 6708.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereedconference proceedings of the Fourth International Conference on Big DataAnalytics, BDA 2015, held in Hyderabad, India, in December 2015. The 9 revised full papers and 9invited papers were carefully reviewed and selected from 61 submissions andcover topics on big data: security and privacy;
Автор: Martin Atzmueller; Alvin Chin; Frederik Janssen; I Название: Big Data Analytics in the Social and Ubiquitous Context ISBN: 3319290088 ISBN-13(EAN): 9783319290089 Издательство: Springer Рейтинг: Цена: 5590.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Using Wikipedia for Cross-language Named Entity Recognition.- On the Predictive Power of Web Intelligence and Social Media.- A Latent Space Analysis of Editor Lifecycles in Wikipedia.- On Spatial Measures of Geographic Relevance for Geotagged Social Media Content.- Formation and Temporal Evolution of Social Groups During Coffee Breaks.- A Habit Detection Algorithm (HDA) for Discovering Recurrent Patterns in Smart Meter Time Series.- RoADS: A road pavement monitoring system for anomaly detection using smart phones.- Mining ticketing logs for usage characterization with nonnegative matrix factorization.- Context-Aware Location Prediction.
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