Introduction to Privacy-Preserving Data Publishing, Fung, Benjamin C.M.
Автор: Thomas Barton Название: Apply Data Science ISBN: 3658387971 ISBN-13(EAN): 9783658387976 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Поставка под заказ.
Описание: This book offers an introduction to the topic of data science based on the visual processing of data. It deals with ethical considerations in the digital transformation and presents a process framework for the evaluation of technologies. It also explains special features and findings on the failure of data science projects and presents recommendation systems in consideration of current developments. Machine learning functionality in business analytics tools is compared and the use of a process model for data science is shown. The integration of renewable energies using the example of photovoltaic systems, more efficient use of thermal energy, scientific literature evaluation, customer satisfaction in the automotive industry and a framework for the analysis of vehicle data serve as application examples for the concrete use of data science. The book offers important information that is just as relevant for practitioners as for students and teachers.
Автор: Chuan Zhang, Tong Wu, Youqi Li, Liehuang Zhu Название: Privacy-Preserving in Mobile Crowdsensing ISBN: 9811983143 ISBN-13(EAN): 9789811983146 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Mobile crowdsensing is a new sensing paradigm that utilizes the intelligence of a crowd of individuals to collect data for mobile purposes by using their portable devices, such as smartphones and wearable devices. Commonly, individuals are incentivized to collect data to fulfill a crowdsensing task released by a data requester. This “sensing as a service” elaborates our knowledge of the physical world by opening up a new door of data collection and analysis. However, with the expansion of mobile crowdsensing, privacy issues urgently need to be solved. In this book, we discuss the research background and current research process of privacy protection in mobile crowdsensing. In the first chapter, the background, system model, and threat model of mobile crowdsensing are introduced. The second chapter discusses the current techniques to protect user privacy in mobile crowdsensing. Chapter three introduces the privacy-preserving content-based task allocation scheme. Chapter four further introduces the privacy-preserving location-based task scheme. Chapter five presents the scheme of privacy-preserving truth discovery with truth transparency. Chapter six proposes the scheme of privacy-preserving truth discovery with truth hiding. Chapter seven summarizes this monograph and proposes future research directions. In summary, this book introduces the following techniques in mobile crowdsensing: 1) describe a randomizable matrix-based task-matching method to protect task privacy and enable secure content-based task allocation; 2) describe a multi-clouds randomizable matrix-based task-matching method to protect location privacy and enable secure arbitrary range queries; and 3) describe privacy-preserving truth discovery methods to support efficient and secure truth discovery. These techniques are vital to the rapid development of privacy-preserving in mobile crowdsensing.
Автор: Zafarani Название: Social Media Mining ISBN: 1107018854 ISBN-13(EAN): 9781107018853 Издательство: Cambridge Academ Рейтинг: Цена: 9027.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Social Media Mining integrates social media, social network analysis, and data mining to provide a coherent platform for students, practitioners, researchers and project managers to understand the basics and potentials of social media mining. It presents fundamental concepts, emerging issues, and effective algorithms for network analysis and data mining.
Автор: Fung, Benjamin C.M. , Wang, Ke , Fu, Ada Wai-Che Название: Introduction to Privacy-Preserving Data Publishing ISBN: 0367383756 ISBN-13(EAN): 9780367383756 Издательство: Taylor&Francis Рейтинг: Цена: 9492.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Gaining access to high-quality data is a vital necessity in knowledge-based decision making. But data in its raw form often contains sensitive information about individuals. Providing solutions to this problem, the methods and tools of privacy-preserving data publishing enable the publication of useful information while protecting data privacy. Introduction to Privacy-Preserving Data Publishing: Concepts and Techniques presents state-of-the-art information sharing and data integration methods that take into account privacy and data mining requirements.
The first part of the book discusses the fundamentals of the field. In the second part, the authors present anonymization methods for preserving information utility for specific data mining tasks. The third part examines the privacy issues, privacy models, and anonymization methods for realistic and challenging data publishing scenarios. While the first three parts focus on anonymizing relational data, the last part studies the privacy threats, privacy models, and anonymization methods for complex data, including transaction, trajectory, social network, and textual data.
This book not only explores privacy and information utility issues but also efficiency and scalability challenges. In many chapters, the authors highlight efficient and scalable methods and provide an analytical discussion to compare the strengths and weaknesses of different solutions.
Автор: Charu C. Aggarwal; Philip S. Yu Название: Privacy-Preserving Data Mining ISBN: 1441943714 ISBN-13(EAN): 9781441943712 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book proposes a number of techniques to perform data mining tasks in a privacy-preserving way. The survey information included with each chapter is unique in terms of its focus on introducing the different topics more comprehensively.
Автор: Leetaru Kalev Название: Data Mining Methods for the Content Analyst ISBN: 0415895146 ISBN-13(EAN): 9780415895149 Издательство: Taylor&Francis Рейтинг: Цена: 6583.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With continuous advancements and an increase in user popularity, data mining technologies serve as an invaluable resource for researchers across a wide range of disciplines in the humanities and social sciences. In this comprehensive guide, author and research scientist Kalev Leetaru introduces the approaches, strategies, and methodologies of current data mining techniques, offering insights for new and experienced users alike. Designed as an instructive reference to computer-based analysis approaches, each chapter of this resource explains a set of core concepts and analytical data mining strategies, along with detailed examples and steps relating to current data mining practices. Every technique is considered with regard to context, theory of operation and methodological concerns, and focuses on the capabilities and strengths relating to these technologies. In addressing critical methodologies and approaches to automated analytical techniques, this work provides an essential overview to a broad innovative field.
Автор: William W. Hsieh Название: Introduction to Environmental Data Science ISBN: 1107065550 ISBN-13(EAN): 9781107065550 Издательство: Cambridge Academ Рейтинг: Цена: 9821.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Statistical and machine learning methods have many applications in the environmental sciences, including prediction and data analysis in meteorology, hydrology and oceanography; pattern recognition for satellite images from remote sensing; management of agriculture and forests; assessment of climate change; and much more. With rapid advances in machine learning in the last decade, this book provides an urgently needed, comprehensive guide to machine learning and statistics for students and researchers interested in environmental data science. It includes intuitive explanations covering the relevant background mathematics, with examples drawn from the environmental sciences. A broad range of topics is covered, including correlation, regression, classification, clustering, neural networks, random forests, boosting, kernel methods, evolutionary algorithms and deep learning, as well as the recent merging of machine learning and physics. End?of?chapter exercises allow readers to develop their problem-solving skills, and online datasets allow readers to practise analysis of real data.
Автор: Gutierrez, Daniel D. Название: Machine learning and data science ISBN: 1634620968 ISBN-13(EAN): 9781634620963 Издательство: Gazelle Book Services Рейтинг: Цена: 10937.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A practitioners tools have a direct impact on the success of his or her work. This book will provide the data scientist with the tools and techniques required to excel with statistical learning methods in the areas of data access, data munging, exploratory data analysis, supervised machine learning, unsupervised machine learning and model evaluation. Machine learning and data science are large disciplines, requiring years of study in order to gain proficiency. This book can be viewed as a set of essential tools we need for a long-term career in the data science field recommendations are provided for further study in order to build advanced skills in tackling important data problem domains. The R statistical environment was chosen for use in this book. R is a growing phenomenon worldwide, with many data scientists using it exclusively for their project work. All of the code examples for the book are written in R. In addition, many popular R packages and data sets will be used.
Автор: James T. Streib; Takako Soma Название: Guide to Data Structures ISBN: 3319700839 ISBN-13(EAN): 9783319700830 Издательство: Springer Рейтинг: Цена: 7406.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This accessible and engaging textbook/guide provides a concise introduction to data structures and associated algorithms. Emphasis is placed on the fundamentals of data structures, enabling the reader to quickly learn the key concepts, and providing a strong foundation for later studies of more complex topics. The coverage includes discussions on stacks, queues, lists, (using both arrays and links), sorting, and elementary binary trees, heaps, and hashing. This content is also a natural continuation from the material provided in the separate Springer title Guide to Java by the same authors.Topics and features: reviews the preliminary concepts, and introduces stacks and queues using arrays, along with a discussion of array-based lists; examines linked lists, the implementation of stacks and queues using references, binary trees, a range of varied sorting techniques, heaps, and hashing; presents both primitive and generic data types in each chapter, and makes use of contour diagrams to illustrate object-oriented concepts; includes chapter summaries, and asks the reader questions to help them interact with the material; contains numerous examples and illustrations, and one or more complete program in every chapter; provides exercises at the end of each chapter, as well as solutions to selected exercises, and a glossary of important terms.
This clearly-written work is an ideal classroom text for a second semester course in programming using the Java programming language, in preparation for a subsequent advanced course in data structures and algorithms. The book is also eminently suitable as a self-study guide in either academe or industry.
Автор: S. Sumathi; S.N. Sivanandam Название: Introduction to Data Mining and its Applications ISBN: 3662500809 ISBN-13(EAN): 9783662500804 Издательство: Springer Рейтинг: Цена: 41787.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining.
Автор: Healy Kieran Название: Data Visualization: A Practical Introduction ISBN: 0691181624 ISBN-13(EAN): 9780691181622 Издательство: Wiley Рейтинг: Цена: 6653.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
An accessible primer on how to create effective graphics from data
This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way.
Data Visualization builds the reader's expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective "small multiple" plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible.
Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings.
Provides hands-on instruction using R and ggplot2
Shows how the "tidyverse" of data analysis tools makes working with R easier and more consistent
Includes a library of data sets, code, and functions
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