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检索条件"丛书名=Studies in Big Data"

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big data in Complex Systems: Challenges and Opportunities 1

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丛书名： studies in big data

2015年

作者： Aboul Ella Hassanien, Ahmad Taher Azar, Vaclav Snasael, Janusz Kacprzyk, Jemal H. Abawajy (eds.)

ISBN: (数字)9783319110554

ISBN: (纸本)9783319110554;9783319110561

This volume provides challenges and Opportunities with updated, in-depth material on the application of big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. data analysis, organization, retrieval, and modeling are otherfoundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.

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Rule Based Systems for big data: A Machine Learning Approach 1st

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丛书名： studies in big data 13

2015年

作者： Han Liu, Alexander Gegov, Mihaela Cocea

ISBN: (纸本)3319236954;9783319236957;9783319236964

The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

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big data Analysis: New Algorithms for a New Society 1st ed. 2016

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丛书名： studies in big data, volume 16

2015年

作者： Nathalie Japkowicz Jerzy Stefanowski

ISBN: (纸本)9783319269870;9783319269894

This edited volume is devoted to big data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that big data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining big data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of big data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by big data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of big data Analysis along with its pitfalls and challenges.

关键词： Machine learning data mining big data

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Granular Computing and Decision-Making: Interactive and Iterative Approaches 1

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丛书名： studies in big data

2015年

作者： Witold Pedrycz, Shyi-Ming Chen (eds.)

ISBN: (数字)9783319168289;9783319168296

ISBN: (纸本)9783319168289;9783319168296

This volume is devoted to interactive and iterative processes of decision-making I2 Fuzzy Decision Making, in brief. Decision-making is inherently interactive. Fuzzy sets help realize human-machine communication in an efficient way by facilitating a two-way interaction in a friendly and transparent manner. Human-centric interaction is of paramount relevance as a leading guiding design principle of decision support systems. The volume provides the reader with an updated and in-depth material on the conceptually appealing and practically sound methodology and practice of I2 Fuzzy Decision Making. The book engages a wealth of methods of fuzzy sets and Granular Computing, brings new concepts, architectures and practice of fuzzy decision-making providing the reader with various application studies. The book is aimed at a broad audience of researchers and practitioners in numerous disciplines in which decision-making processes play a pivotal role and serve as a vehicle to produce solutions to existing problems. Those involved in operations research, management, various branches of engineering, social sciences, logistics, and economics will benefit from the exposure to the subject matter. The book may serve as a useful and timely reference material for graduate students and senior undergraduate students in courses on decision-making, Computational Intelligence, operations research, pattern recognition, risk management, and knowledge-based systems.

关键词： Fuzzy decision making. Granular computing.

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Operations Research and big data: IO2015-XVII Congress of Portuguese Association of Operational Research (APDIO) 1

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丛书名： studies in big data 15

2015年

作者： Ana Paula Ferreira Dias Barbosa Póvoa, Joao Luis de Miranda (eds.)

ISBN: (数字)9783319241548

ISBN: (纸本)9783319241524;9783319241548

The development of Operations Research (OR) requires constant improvements, such as the integration of research results with business applications and innovative educational practice. The full deployment and commercial exploitation of goods and services generally need the construction of strong synergies between educational institutions and businesses. The IO2015 -XVII Congress of APDIO aims at strengthening the knowledge triangle in education, research and innovation, in order to maximize the contribution of OR for sustainable growth, the promoting of a knowledge-based economy, and the smart use of finite resources. The IO2015-XVII Congress of APDIO is a privileged meeting point for the promotion and dissemination of OR and related disciplines, through the exchange of ideas among teachers, researchers, students , and professionals with different background, but all sharing a common desire that is the development of OR.

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Mastering data-Intensive Collaboration and Decision Making 2014

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丛书名： studies in big data

2014年

作者： Nikos Karacapilidis

ISBN: (数字)9783319026121

ISBN: (纸本)9783319026114

This book reports on cutting-edge research carried out within the context of the EU-funded Dicode project, which aims at facilitating and augmenting collaboration and decision making in data-intensive and cognitively complex settings. Whenever appropriate, Dicode builds on prominent high-performance computing paradigms and large data processing technologies to meaningfully search, analyze, and aggregate data from diverse, extremely large and rapidly evolving sources. The Dicode approach and services are fully explained and particular emphasis is placed on deepening insights regarding the exploitation of big data, as well as on collaboration and issues relating to sense-making support. Building on current advances, the solution developed in the Dicode project brings together the reasoning capabilities of both the machine and humans. It can be viewed as an innovative workbench incorporating and orchestrating a set of interoperable services that reduce the data intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and effective in their work practices.

关键词： data mining. big data. Decision support systems. Teams in the workplace data processing.

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data Mining for Service 1

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丛书名： studies in big data

2014年

作者： Katsutoshi Yada (auth.), Katsutoshi Yada (eds.)

ISBN: (数字)9783642452529

ISBN: (纸本)9783642452512;9783642452529

Virtually all nontrivial and modern service related problems and systems involve data volumes and types that clearly fall into what is presently meant as "big data", that is, are huge, heterogeneous, complex, distributed, etc. data mining is a series of processes which include collecting and accumulating data, modeling phenomena, and discovering new information, and it is one of the most important steps to scientific analysis of the processes of services. data mining application in services requires a thorough understanding of the characteristics of each service and knowledge of the compatibility of data mining technology within each particular service, rather than knowledge only in calculation speed and prediction accuracy. Varied examples of services provided in this book will help readers understand the relation between services and data mining technology. This book is intended to stimulate interest among researchers and practitioners in the relation between data mining technology and its application to other fields.

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Molecular Computing 2014

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丛书名： studies in big data

2014年

作者： Weng-Long Chang Athanasios V. Vasilakos

ISBN: (数字)9783319051222

ISBN: (纸本)9783319051215

This textbook introduces a concise approach to the design of molecular algorithms for students or researchers who are interested in dealing with complex problems. Through numerous examples and exercises, you will understand the main difference of molecular circuits and traditional digital circuits to manipulate the same problem and you will also learn how to design a molecular algorithm of solving any a problem from start to finish. The book starts with an introduction to computational aspects of digital computers and molecular computing, data representation of molecular computing, molecular operations of molecular computing and number representation of molecular computing and provides many molecular algorithm to construct the parity generator and the parity checker of error-detection codes on digital communication, to encode integers of different formats, single precision and double precision of floating-point numbers, to implement addition and subtraction of unsigned integers, to construct logic operations including NOT, OR, AND, NOR, NAND, Exclusive-OR (XOR) and Exclusive-NOR (XNOR), to implement comparators, shifters, increase, decrease, and to complete two specific operations that are to find the maximum number of 1 and to find the minimum number of 1. The book is also a useful reference source to people new for the field of molecular computing.

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Astronomy and big data: A data Clustering Approach to Identifying Uncertain Galaxy Morphology 1

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丛书名： studies in big data

2014年

作者： Kieran Jay Edwards, Mohamed Medhat Gaber (auth.)

ISBN: (数字)9783319065991

ISBN: (纸本)9783319065984;9783319065991

With the onset of massive cosmological data collection through media such as the Sloan Digital Sky Survey (SDSS), galaxy classification has been accomplished for the most part with the help of citizen science communities like Galaxy Zoo. Seeking the wisdom of the crowd for such big data processing has proved extremely beneficial. However, an analysis of one of the Galaxy Zoo morphological classification data sets has shown that a significant majority of all classified galaxies are labelled as Uncertain. This book reports on how to use data mining, more specifically clustering, to identify galaxies that the public has shown some degree of uncertainty for as to whether they belong to one morphology type or another. The book shows the importance of transitions between different data mining techniques in an insightful workflow. It demonstrates that Clustering enables to identify discriminating features in the analysed data sets, adopting a novel feature selection algorithms called Incremental Feature Selection (IFS). The book shows the use of state-of-the-art classification techniques, Random Forests and Support Vector Machines to validate the acquired results. It is concluded that a vast majority of these galaxies are, in fact, of spiral morphology with a small subset potentially consisting of stars, elliptical galaxies or galaxies of other morphological variants.

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Comparative Efficiency in data Envelopment Analysis Based on Ratio Analysis 1

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丛书名： studies in big data

1000年

作者： Farhad Hosseinzadeh Lotfi Tofigh Allahviranloo Witold Pedrycz Mohammad Reza Mozaffari Javad Gerami

ISBN: (数字)9783031431814

ISBN: (纸本)9783031431807;9783031431838

The combination of DEA and ratio analysis is introduced as a suitable field for evaluating the performance of DMUs. In this regard, DEA-R is also proposed as a hybrid technique for calculating efficiency, ranking DMUs, and finding efficient faces. Therefore, the relationship between DEA and DEA-R provides a suitable field for researchers in the field of evaluating the performance of DMUs. The audience of this book is not limited to researchers in mathematics fields, but experts and students in industrial engineering and management fields also benefit from the topics of this book.

关键词： data Engineering Computational Intelligence big data

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