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Mobility, Data Mining and Privacy, Fosca Giannotti; Dino Pedreschi


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Цена: 19564.00р.
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Автор: Fosca Giannotti; Dino Pedreschi
Название:  Mobility, Data Mining and Privacy
ISBN: 9783642094439
Издательство: Springer
Классификация:



ISBN-10: 3642094430
Обложка/Формат: Paperback
Страницы: 410
Вес: 0.59 кг.
Дата издания: 19.10.2010
Язык: English
Размер: 234 x 156 x 22
Основная тема: Computer Science
Подзаголовок: Geographic Knowledge Discovery
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Mobile communications and ubiquitous computing generate large volumes of data. The editors manage a research project called GeoPKDD, Geographic Privacy-Aware Knowledge Discovery and Delivery, and this book relates their findings in 13 chapters covering all related subjects.


Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking

Автор: Foster Provost
Название: Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking
ISBN: 1449361323 ISBN-13(EAN): 9781449361327
Издательство: Wiley
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Цена: 6334.00 р.
Наличие на складе: Есть (1 шт.)
Описание: This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect.

Data Mining for Dummies

Автор: Brown Meta S.
Название: Data Mining for Dummies
ISBN: 1118893174 ISBN-13(EAN): 9781118893173
Издательство: Wiley
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Цена: 5067.00 р.
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Описание: Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum.

Data and Applications Security and Privacy XXX

Автор: Ranise
Название: Data and Applications Security and Privacy XXX
ISBN: 3319414828 ISBN-13(EAN): 9783319414829
Издательство: Springer
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Цена: 10482.00 р.
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Описание: This book constitutes the refereed proceedings of the 30th Annual IFIP WG 11.3 International Working Conference on Data and Applications Security and Privacy, DBSec 2016, held in trento, Itlay, in July 2016.

Data Privacy Management and Autonomous Spontaneous Security

Автор: Joaquin Garcia-Alfaro; Guillermo Navarro-Arribas;
Название: Data Privacy Management and Autonomous Spontaneous Security
ISBN: 3642112064 ISBN-13(EAN): 9783642112065
Издательство: Springer
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Цена: 9781.00 р.
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Описание: 4th International Workshop DPM 2009 and Second International Workshop SETOP 2009 St Malo France Sep. .

Data and Applications Security and Privacy XXXI

Автор: Giovanni Livraga; Sencun Zhu
Название: Data and Applications Security and Privacy XXXI
ISBN: 3319611755 ISBN-13(EAN): 9783319611754
Издательство: Springer
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Цена: 11179.00 р.
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Описание: This book constitutes the refereed proceedings of the 31st Annual IFIP WG 11.3 International Working Conference on Data and Applications Security and Privacy, DBSec 2017, held in Philadelphia, PA, USA, in July 2017. The 21 full papers and 9 short papers presented were carefully reviewed and selected from 59 submissions.

Mobility Data Management and Exploration

Автор: Nikos Pelekis; Yannis Theodoridis
Название: Mobility Data Management and Exploration
ISBN: 1493945106 ISBN-13(EAN): 9781493945108
Издательство: Springer
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Цена: 8384.00 р.
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Описание: This text integrates different mobility data handling processes, from database management to multi-dimensional analysis and mining, into a unified presentation driven by the spectrum of requirements raised by real-world applications.

Data Mining: Practical Machine Learning Tools and Techniques,

Автор: Ian H. Witten
Название: Data Mining: Practical Machine Learning Tools and Techniques,
ISBN: 0123748569 ISBN-13(EAN): 9780123748560
Издательство: Elsevier Science
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Цена: 8695.00 р.
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Описание: Like the popular second edition, Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining?including both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. <br><br>Complementing the book is a fully functional platform-independent open source Weka software for machine learning, available for free download. <br><br>The book is a major revision of the second edition that appeared in 2005. While the basic core remains the same, it has been updated to reflect the changes that have taken place over the last four or five years. The highlights for the updated new edition include completely revised technique sections; new chapter on Data Transformations, new chapter on Ensemble Learning, new chapter on Massive Data Sets, a new ?book release? version of the popular Weka machine learning open source software (developed by the authors and specific to the Third Edition); new material on ?multi-instance learning?; new information on ranking the classification, plus comprehensive updates and modernization throughout. All in all, approximately 100 pages of new material.<br> <br><br>* Thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques<br><br>* Algorithmic methods at the heart of successful data mining?including tired and true methods as well as leading edge methods<br><br>* Performance improvement techniques that work by transforming the input or output<br><br>* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization?in an updated, interactive interface. <br>

Data Mining: The Textbook

Автор: С.Aggarwal
Название: Data Mining: The Textbook
ISBN: 3319141414 ISBN-13(EAN): 9783319141411
Издательство: Springer
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Цена: 9781.00 р.
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Описание: This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues.

Privacy-Preserving Data Mining

Автор: Charu C. Aggarwal; Philip S. Yu
Название: Privacy-Preserving Data Mining
ISBN: 1441943714 ISBN-13(EAN): 9781441943712
Издательство: Springer
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Цена: 27251.00 р.
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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.

Statistical and Machine-Learning Data Mining

Автор: Ratner Bruce
Название: Statistical and Machine-Learning Data Mining
ISBN: 1439860912 ISBN-13(EAN): 9781439860915
Издательство: Taylor&Francis
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Цена: 9033.00 р.
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Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.

Data Mining with R

Автор: Torgo
Название: Data Mining with R
ISBN: 1439810184 ISBN-13(EAN): 9781439810187
Издательство: Taylor&Francis
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Цена: 9951.00 р.
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Описание: This hands-on book uses practical examples to illustrate the power of R and data mining. Assuming no prior knowledge of R or data mining/statistical techniques, it covers a diverse set of problems that pose different challenges in terms of size, type of data, goals of analysis, and analytical tools. The main data mining processes and techniques are presented through detailed, real-world case studies. With these case studies, the author supplies all necessary steps, code, and data. Mirroring the do-it-yourself approach of the text, the supporting website provides data sets and R code.

Matrix Methods in Data Mining and Pattern Recognition

Автор: Lars Eld?n
Название: Matrix Methods in Data Mining and Pattern Recognition
ISBN: 0898716268 ISBN-13(EAN): 9780898716269
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB. In Part II, linear algebra techniques are applied to data mining problems. Part III is a brief introduction to eigenvalue and singular value algorithms. The applications discussed include classification of handwritten digits, text mining, text summarization, pagerank computations related to the Google search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book.


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