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Managing and Mining Sensor Data, Charu C. Aggarwal


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Автор: Charu C. Aggarwal
Название:  Managing and Mining Sensor Data
ISBN: 9781489992383
Издательство: Springer
Классификация:



ISBN-10: 1489992383
Обложка/Формат: Paperback
Страницы: 534
Вес: 0.76 кг.
Дата издания: 26.06.2015
Язык: English
Размер: 234 x 156 x 28
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process.

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: 42230.00 T
Наличие на складе: Есть
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.

Transparent data mining for big and small data.

Автор: Cerquitelli, Tania, Quercia, Daniele, Pasquale, Frank (Eds.)
Название: Transparent data mining for big and small data.
ISBN: 3319540238 ISBN-13(EAN): 9783319540238
Издательство: Springer
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Цена: 111790.00 T
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Описание: This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions.

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: 60190.00 T
Наличие на складе: Поставка под заказ.
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.

Data Mining and Knowledge Discovery via Logic-Based Methods

Автор: Evangelos Triantaphyllou
Название: Data Mining and Knowledge Discovery via Logic-Based Methods
ISBN: 1441916296 ISBN-13(EAN): 9781441916297
Издательство: Springer
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Цена: 153720.00 T
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Описание: This book uses a novel method to study a series of interconnected key data mining and knowledge discovery problems in depth and in a way that stimulates the quest for more knowledge. It also presents a collection of examples, many from real-life applications.

Association Rule Hiding for Data Mining

Автор: Aris Gkoulalas-Divanis; Vassilios S. Verykios
Название: Association Rule Hiding for Data Mining
ISBN: 1441965688 ISBN-13(EAN): 9781441965684
Издательство: Springer
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Цена: 121110.00 T
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Описание:

Privacy and security risks arising from the application of different data mining techniques to large institutional data repositories have been solely investigated by a new research domain, the so-called privacy preserving data mining. Association rule hiding is a new technique in data mining, which studies the problem of hiding sensitive association rules from within the data.

Association Rule Hiding for Data Mining addresses the problem of "hiding" sensitive association rules, and introduces a number of heuristic solutions. Exact solutions of increased time complexity that have been proposed recently are presented, as well as a number of computationally efficient (parallel) approaches that alleviate time complexity problems, along with a thorough discussion regarding closely related problems (inverse frequent item set mining, data reconstruction approaches, etc.). Unsolved problems, future directions and specific examples are provided throughout this book to help the reader study, assimilate and appreciate the important aspects of this challenging problem.

Association Rule Hiding for Data Mining is designed for researchers, professors and advanced-level students in computer science studying privacy preserving data mining, association rule mining, and data mining. This book is also suitable for practitioners working in this industry.


Agents and Data Mining Interaction

Автор: Longbing Cao; A.E. Gorodetsky; Jiming Liu; Gerhard
Название: Agents and Data Mining Interaction
ISBN: 3642036023 ISBN-13(EAN): 9783642036026
Издательство: Springer
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Цена: 65210.00 T
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Описание: 4th International Workshop on Agents and Data Mining Interaction ADMI 2009 Budapest Hungary May 101. .

Foundations and Novel Approaches in Data Mining

Автор: Tsau Young Lin; Setsuo Ohsuga; Churn-Jung Liau; Xi
Название: Foundations and Novel Approaches in Data Mining
ISBN: 364206650X ISBN-13(EAN): 9783642066504
Издательство: Springer
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Цена: 204040.00 T
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Описание: Data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this volume, we hope to remedy problems by (1) presenting a theoretical foundation of data-mining, and (2) providing important new directions for data-mining research.

Managing and Mining Sensor Data

Автор: Charu C. Aggarwal
Название: Managing and Mining Sensor Data
ISBN: 1461463084 ISBN-13(EAN): 9781461463085
Издательство: Springer
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Цена: 93160.00 T
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Описание: Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process.

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: 65210.00 T
Наличие на складе: Поставка под заказ.
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.

Managing and Mining Graph Data

Автор: Charu C. Aggarwal; Haixun Wang
Название: Managing and Mining Graph Data
ISBN: 1461425603 ISBN-13(EAN): 9781461425601
Издательство: Springer
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Цена: 181670.00 T
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Описание: Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy.

Managing and Mining Graph Data

Автор: Charu C. Aggarwal; Haixun Wang
Название: Managing and Mining Graph Data
ISBN: 1441960449 ISBN-13(EAN): 9781441960443
Издательство: Springer
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Цена: 167700.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy.

Managing and Mining Uncertain Data

Автор: Charu C. Aggarwal
Название: Managing and Mining Uncertain Data
ISBN: 1441935177 ISBN-13(EAN): 9781441935175
Издательство: Springer
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Цена: 121110.00 T
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Описание: This collection of surveys presents the most recent models, algorithms and applications in mining uncertain data. Organized to make it more accessible to applications-driven practitioners, it includes case studies based on real-world examples.


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