Statistical Analysis of Massive Data Streams

Statistical Analysis of Massive Data Streams PDF Author: National Research Council
Publisher: National Academies Press
ISBN: 0309182107
Category : Computers
Languages : en
Pages : 531

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Book Description
Massive data streams, large quantities of data that arrive continuously, are becoming increasingly commonplace in many areas of science and technology. Consequently development of analytical methods for such streams is of growing importance. To address this issue, the National Security Agency asked the NRC to hold a workshop to explore methods for analysis of streams of data so as to stimulate progress in the field. This report presents the results of that workshop. It provides presentations that focused on five different research areas where massive data streams are present: atmospheric and meteorological data; high-energy physics; integrated data systems; network traffic; and mining commercial data streams. The goals of the report are to improve communication among researchers in the field and to increase relevant statistical science activity.

Statistical Analysis of Massive Data Streams

Statistical Analysis of Massive Data Streams PDF Author: National Research Council
Publisher: National Academies Press
ISBN: 0309182107
Category : Computers
Languages : en
Pages : 531

Get Book Here

Book Description
Massive data streams, large quantities of data that arrive continuously, are becoming increasingly commonplace in many areas of science and technology. Consequently development of analytical methods for such streams is of growing importance. To address this issue, the National Security Agency asked the NRC to hold a workshop to explore methods for analysis of streams of data so as to stimulate progress in the field. This report presents the results of that workshop. It provides presentations that focused on five different research areas where massive data streams are present: atmospheric and meteorological data; high-energy physics; integrated data systems; network traffic; and mining commercial data streams. The goals of the report are to improve communication among researchers in the field and to increase relevant statistical science activity.

Frontiers in Massive Data Analysis

Frontiers in Massive Data Analysis PDF Author: National Research Council
Publisher: National Academies Press
ISBN: 0309287812
Category : Mathematics
Languages : en
Pages : 191

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Book Description
Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.

Mining of Massive Datasets

Mining of Massive Datasets PDF Author: Jure Leskovec
Publisher: Cambridge University Press
ISBN: 1107077230
Category : Computers
Languages : en
Pages : 480

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Book Description
Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.

Data Streams

Data Streams PDF Author: S. Muthukrishnan
Publisher: Now Publishers Inc
ISBN: 193301914X
Category : Computers
Languages : en
Pages : 136

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Book Description
In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time, and number of passes. Some of the methods rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity. The applications for this scenario include IP network traffic analysis, mining text message streams and processing massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges.

Machine Learning for Data Streams

Machine Learning for Data Streams PDF Author: Albert Bifet
Publisher: MIT Press
ISBN: 0262346052
Category : Computers
Languages : en
Pages : 262

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Book Description
A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.

Research Methodologies in Translation Studies

Research Methodologies in Translation Studies PDF Author: Gabriela Saldanha
Publisher: Routledge
ISBN: 1317641175
Category : Language Arts & Disciplines
Languages : en
Pages : 292

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Book Description
As an interdisciplinary area of research, translation studies attracts students and scholars with a wide range of backgrounds, who then need to face the challenge of accounting for a complex object of enquiry that does not adapt itself well to traditional methods in other fields of investigation. This book addresses the needs of such scholars – whether they are students doing research at postgraduate level or more experienced researchers who want to familiarize themselves with methods outside their current field of expertise. The book promotes a discerning and critical approach to scholarly investigation by providing the reader not only with the know-how but also with insights into how new questions can be fruitfully explored through the coherent integration of different methods of research. Understanding core principles of reliability, validity and ethics is essential for any researcher no matter what methodology they adopt, and a whole chapter is therefore devoted to these issues. Research Methodologies in Translation Studies is divided into four different chapters, according to whether the research focuses on the translation product, the process of translation, the participants involved or the context in which translation takes place. An introductory chapter discusses issues of reliability, credibility, validity and ethics. The impact of our research depends not only on its quality but also on successful dissemination, and the final chapter therefore deals with what is also generally the final stage of the research process: producing a research report.

Decision Management: Concepts, Methodologies, Tools, and Applications

Decision Management: Concepts, Methodologies, Tools, and Applications PDF Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 152251838X
Category : Business & Economics
Languages : en
Pages : 2350

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Book Description
The implementation of effective decision making protocols is crucial in any organizational environment in modern society. Emerging advancements in technology and analytics have optimized uses and applications of decision making systems. Decision Management: Concepts, Methodologies, Tools, and Applications is a compendium of the latest academic material on the control, support, usage, and strategies for implementing efficient decision making systems across a variety of industries and fields. Featuring comprehensive coverage on numerous perspectives, such as data visualization, pattern analysis, and predictive analytics, this multi-volume book is an essential reference source for researchers, academics, professionals, managers, students, and practitioners interested in the maintenance and optimization of decision management processes.

Big Data Analytics

Big Data Analytics PDF Author: Saumyadipta Pyne
Publisher: Springer
ISBN: 8132236289
Category : Computers
Languages : en
Pages : 278

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Book Description
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.

Statistical Problems in Particle Physics, Astrophysics and Cosmology

Statistical Problems in Particle Physics, Astrophysics and Cosmology PDF Author: Louis Lyons
Publisher: Imperial College Press
ISBN: 1860946496
Category : Science
Languages : en
Pages : 326

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Book Description
These proceedings comprise current statistical issues in analyzing data in particle physics, astrophysics and cosmology, as discussed at the PHYSTAT05 conference in Oxford. This is a continuation of the popular PHYSTAT series; previous meetings were held at CERN (2000), Fermilab (2000), Durham (2002) and Stanford (2003).In-depth discussions on topical issues are presented by leading statisticians and research workers in their relevant fields. Included are invited reviews and contributed research papers presenting the latest, state-of-the-art techniques.

Internet of Things and Big Data Analytics Toward Next-Generation Intelligence

Internet of Things and Big Data Analytics Toward Next-Generation Intelligence PDF Author: Nilanjan Dey
Publisher: Springer
ISBN: 331960435X
Category : Technology & Engineering
Languages : en
Pages : 545

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Book Description
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.