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Intelligent Data Analysis for e-Learning, Miguel, Jorge


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Цена: 15159.00р.
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Автор: Miguel, Jorge
Название:  Intelligent Data Analysis for e-Learning
ISBN: 9780128045350
Издательство: Elsevier Science
Классификация:


ISBN-10: 0128045353
Обложка/Формат: Paperback
Страницы: 220
Вес: 0.42 кг.
Дата издания: 09.08.2016
Серия: Intelligent data-centric systems
Язык: English
Размер: 194 x 234 x 10
Подзаголовок: Enhancing security and trustworthiness in online learning systems
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание:

Intelligent Data Analysis for e-Learning: Enhancing Security and Trustworthiness in Online Learning Systems addresses information security within e-Learning based on trustworthiness assessment and prediction. Over the past decade, many learning management systems have appeared in the education market. Security in these systems is essential for protecting against unfair and dishonest conduct-most notably cheating-however, e-Learning services are often designed and implemented without considering security requirements.

This book provides functional approaches of trustworthiness analysis, modeling, assessment, and prediction for stronger security and support in online learning, highlighting the security deficiencies found in most online collaborative learning systems. The book explores trustworthiness methodologies based on collective intelligence than can overcome these deficiencies. It examines trustworthiness analysis that utilizes the large amounts of data-learning activities generate. In addition, as processing this data is costly, the book offers a parallel processing paradigm that can support learning activities in real-time.

The book discusses data visualization methods for managing e-Learning, providing the tools needed to analyze the data collected. Using a case-based approach, the book concludes with models and methodologies for evaluating and validating security in e-Learning systems.

Indexing: The books of this series are submitted to EI-Compendex and SCOPUS


  • Provides guidelines for anomaly detection, security analysis, and trustworthiness of data processing
  • Incorporates state-of-the-art, multidisciplinary research on online collaborative learning, social networks, information security, learning management systems, and trustworthiness prediction
  • Proposes a parallel processing approach that decreases the cost of expensive data processing
  • Offers strategies for ensuring against unfair and dishonest assessments
  • Demonstrates solutions using a real-life e-Learning context



Advances in Intelligent Data Analysis VII

Автор: Michael R. Berthold; John Shawe-Taylor; Nada Lavra
Название: Advances in Intelligent Data Analysis VII
ISBN: 3540748245 ISBN-13(EAN): 9783540748243
Издательство: Springer
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Цена: 10480.00 р.
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Описание: Constitutes the proceedings of the 7th International Conference on Intelligent Data Analysis, IDA 2007, held in Ljubljana, Slovenia, September 6-8, 2007. This book includes statistics, machine learning, data mining, classification and pattern recognition, clustering, applications, modeling, and interactive dynamic data visualization.

Intelligent Data Engineering and Automated Learning - IDEAL 2007

Автор: Xin Yao; Hujun Yin; Peter Tino; Emilio Corchado; W
Название: Intelligent Data Engineering and Automated Learning - IDEAL 2007
ISBN: 3540772251 ISBN-13(EAN): 9783540772255
Издательство: Springer
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Цена: 22359.00 р.
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Описание: Constitutes the refereed proceedings of the 8th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2007, held in Birmingham, UK, in December 2007. This book presents 170 revised full papers that were reviewed and selected from more than 270 submissions.

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>

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 Analysis Using SQL and Excel

Автор: Linoff Gordon S.
Название: Data Analysis Using SQL and Excel
ISBN: 111902143X ISBN-13(EAN): 9781119021438
Издательство: Wiley
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Цена: 6178.00 р.
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Описание: A practical guide to data mining using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis SQL and Excel to perform sophisticated data analysis without the need for complex and expensive data mining tools.

Data Mining and Crime Analysis in Financial Markets

Автор: Marius-Christian Frunza
Название: Data Mining and Crime Analysis in Financial Markets
ISBN: 0128012218 ISBN-13(EAN): 9780128012215
Издательство: Elsevier Science
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Цена: 12462.00 р.
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Описание:

Introduction to the Theories and Varieties of Modern Crime in Financial Markets explores statistical methods and data mining techniques that, if used correctly, can help with crime detection and prevention. The three sections of the book present the methods, techniques, and approaches for recognizing, analyzing, and ultimately detecting and preventing financial frauds, especially complex and sophisticated crimes that characterize modern financial markets.

The first two sections appeal to readers with technical backgrounds, describing data analysis and ways to manipulate markets and commit crimes. The third section gives life to the information through a series of interviews with bankers, regulators, lawyers, investigators, rogue traders, and others.

The book is sharply focused on analyzing the origin of a crime from an economic perspective, showing Big Data in action, noting both the pros and cons of this approach.

Learning Spark: Lightning-Fast Big Data Analytics

Автор: Hamstra Mark, Zaharia Matei
Название: Learning Spark: Lightning-Fast Big Data Analytics
ISBN: 1449358624 ISBN-13(EAN): 9781449358624
Издательство: Wiley
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Цена: 5067.00 р.
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Описание: Written by the developers of Spark, this book will have data scientists and engineers up and running in no time.

Handbook of Data Mining and Learning Analytics

Автор: ElAtia Samira
Название: Handbook of Data Mining and Learning Analytics
ISBN: 1118998235 ISBN-13(EAN): 9781118998236
Издательство: Wiley
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Цена: 17258.00 р.
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Описание: Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates.

Data Mining and Predictive Analysis

Автор: Colleen McCue
Название: Data Mining and Predictive Analysis
ISBN: 0128002298 ISBN-13(EAN): 9780128002292
Издательство: Elsevier Science
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Цена: 9936.00 р.
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Описание: Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than being reactive,security agencies can anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive Analysis offers a clear, practical starting point for professionals who need to use data mining inhomeland security, security analysis, and operational law enforcementsettings.This revised text highlights new and emerging technology, discusses the importance of analytic contextfor ensuring successful implementation of advanced analytics in the operational setting, and covers new analytic service delivery models that increase ease of use and access to high-end technology and analytic capabilities. The use of predictive analytics inintelligence and securityanalysis enables the development of meaningful, information based tactics, strategy, and policy decisions in the operational public safety and security environment.


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