Intelligent Data Analysis for e Learning

Produk Detail:
  • Author : Jorge Miguel
  • Publisher : Morgan Kaufmann
  • Pages : 192 pages
  • ISBN : 0128045450
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Intelligent Data Analysis for e Learning

Download or Read online Intelligent Data Analysis for e Learning full in PDF, ePub and kindle. this book written by Jorge Miguel and published by Morgan Kaufmann which was released on 06 September 2016 with total page 192 pages. We cannot guarantee that Intelligent Data Analysis for e Learning book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Intelligent Data Analysis for e Learning

Intelligent Data Analysis for e Learning
  • Author : Jorge Miguel,Santi Caballé,Fatos Xhafa
  • Publisher : Morgan Kaufmann
  • Release : 06 September 2016
GET THIS BOOK Intelligent Data Analysis for e Learning

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

Intelligent Systems and Learning Data Analytics in Online Education

Intelligent Systems and Learning Data Analytics in Online Education
  • Author : Santi Caballé,Stavros N. Demetriadis,Eduardo Gómez-Sánchez,Pantelis M. Papadopoulos,Armin Weinberger
  • Publisher : Academic Press
  • Release : 15 June 2021
GET THIS BOOK Intelligent Systems and Learning Data Analytics in Online Education

Intelligent Systems and Learning Data Analytics in Online Education provides novel artificial intelligence (AI) and analytics-based methods to improve online teaching and learning. This book addresses key problems such as attrition and lack of engagement in MOOCs and online learning in general. This book explores the state of the art of artificial intelligence, software tools and innovative learning strategies to provide better understanding and solutions to the various challenges of current e-learning in general and MOOC education. In particular, Intelligent

Advances in Intelligent Data Analysis V

Advances in Intelligent Data Analysis V
  • Author : ge International Conference on Intelligent Data Analysis 2003 Berlin
  • Publisher : Springer Science & Business Media
  • Release : 21 August 2003
GET THIS BOOK Advances in Intelligent Data Analysis V

This book constitutes the refereed proceedings of the 5th International Conference on Intelligent Data Analysis, IDA 2003, held in Berlin, Germany in August 2003. The 56 revised papers presented were carefully reviewed and selected from 180 submissions. The papers are organized in topical sections on machine learning, probability and topology, classification and pattern recognition, clustering, applications, modeling, and data processing.

Intelligent Data analysis and its Applications Volume I

Intelligent Data analysis and its Applications  Volume I
  • Author : Jeng-Shyang Pan,Vaclav Snasel,Emilio S. Corchado,Ajith Abraham,Shyue-Liang Wang
  • Publisher : Springer
  • Release : 26 May 2014
GET THIS BOOK Intelligent Data analysis and its Applications Volume I

This volume presents the proceedings of the First Euro-China Conference on Intelligent Data Analysis and Applications (ECC 2014), which was hosted by Shenzhen Graduate School of Harbin Institute of Technology and was held in Shenzhen City on June 13-15, 2014. ECC 2014 was technically co-sponsored by Shenzhen Municipal People’s Government, IEEE Signal Processing Society, Machine Intelligence Research Labs, VSB-Technical University of Ostrava (Czech Republic), National Kaohsiung University of Applied Sciences (Taiwan), and Secure E-commerce Transactions (Shenzhen) Engineering Laboratory of Shenzhen Institute of

Intelligent Data Analysis

Intelligent Data Analysis
  • Author : Deepak Gupta,Siddhartha Bhattacharyya,Ashish Khanna,Kalpna Sagar
  • Publisher : John Wiley & Sons
  • Release : 07 July 2020
GET THIS BOOK Intelligent Data Analysis

This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension, and emphasis will also be given to solving of problems which result from automated data collection, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and so on. This book aims to describe the different approaches of Intelligent Data Analysis from a practical point of view: solving common life problems

Intelligent Data Analysis

Intelligent Data Analysis
  • Author : Michael Berthold,David J Hand
  • Publisher : Springer Science & Business Media
  • Release : 17 April 2013
GET THIS BOOK Intelligent Data Analysis

This is a detailed introductory presentation of the key classes of intelligent data analysis (IDA) methods. The first part of the book discusses classical statistical issues. The following chapters concentrate on machine learning and artificial intelligence and provide introductions to the topics of rule induction methods, neural networks, fuzzy logic, and stochastic search methods. The book concludes with a higher level overview of the IDA process and illustrations of its application.

Proceedings of the Fifth Euro China Conference on Intelligent Data Analysis and Applications

Proceedings of the Fifth Euro China Conference on Intelligent Data Analysis and Applications
  • Author : Pavel Krömer,Hong Zhang,Yongquan Liang,Jeng-Shyang Pan
  • Publisher : Springer
  • Release : 24 December 2018
GET THIS BOOK Proceedings of the Fifth Euro China Conference on Intelligent Data Analysis and Applications

This volume of Advances in Intelligent Systems and Computing highlights papers presented at the Fifth Euro-China Conference on Intelligent Data Analysis and Applications (ECC2018), held in Xi’an, China from October 12 to 14 2018. The conference was co-sponsored by Springer, Xi’an University of Posts and Telecommunications, VSB Technical University of Ostrava (Czech Republic), Fujian University of Technology, Fujian Provincial Key Laboratory of Digital Equipment, Fujian Provincial Key Lab of Big Data Mining and Applications, and Shandong University of Science and Technology

Intelligent Data Analysis and Applications

Intelligent Data Analysis and Applications
  • Author : Jeng-Shyang Pan,Václav Snášel,Tien-Wen Sung,Xiao Dong Wang
  • Publisher : Springer
  • Release : 19 October 2016
GET THIS BOOK Intelligent Data Analysis and Applications

This book gathers papers presented at the ECC 2016, the Third Euro-China Conference on Intelligent Data Analysis and Applications, which was held in Fuzhou City, China from November 7 to 9, 2016. The aim of the ECC is to provide an internationally respected forum for scientific research in the broad areas of intelligent data analysis, computational intelligence, signal processing, and all associated applications of artificial intelligence (AI). The third installment of the ECC was jointly organized by Fujian University of Technology, China, and VSB-Technical

Advances in Intelligent Data Analysis XI

Advances in Intelligent Data Analysis XI
  • Author : Jaakko Hollmen,Frank Klawonn,Allan Tucker
  • Publisher : Springer
  • Release : 20 October 2012
GET THIS BOOK Advances in Intelligent Data Analysis XI

This book constitutes the refereed proceedings of the 11th International Conference on Intelligent Data Analysis, IDA 2012, held in Helsinki, Finland, in October 2012. The 32 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 88 submissions. All current aspects of intelligent data analysis are addressed, including intelligent support for modeling and analyzing data from complex, dynamical systems. The papers focus on novel applications of IDA techniques to, e.g., networked digital information systems; novel modes of data acquisition

Advances in Intelligent Data Analysis V

Advances in Intelligent Data Analysis V
  • Author : Michael R. Berthold,Hans-Joachim Lenz,Elizabeth Bradley,Rudolf Kruse,Christian Borgelt
  • Publisher : Springer
  • Release : 16 March 2011
GET THIS BOOK Advances in Intelligent Data Analysis V

We are glad to present the proceedings of the 5th biennial conference in the Intelligent Data Analysis series. The conference took place in Berlin, Germany, August 28–30, 2003. IDA has by now clearly grown up. Started as a small si- symposium of a larger conference in 1995 in Baden-Baden (Germany) it quickly attractedmoreinterest(bothsubmission-andattendance-wise),andmovedfrom London (1997) to Amsterdam (1999), and two years ago to Lisbon. Submission ratesalongwiththeeverimprovingqualityofpapershaveenabledtheor- nizers to assemble increasingly consistent and high-quality programs. This year we were again overwhelmed by yet another

Advances in Intelligent Data Analysis XIX

Advances in Intelligent Data Analysis XIX
  • Author : Pedro Henriques Abreu,Pedro Pereira Rodrigues,Alberto Fernández (Computer scientist),João Gama
  • Publisher : Springer Nature
  • Release : 26 October 2021
GET THIS BOOK Advances in Intelligent Data Analysis XIX

This book constitutes the proceedings of the 19th International Symposium on Intelligent Data Analysis, IDA 2021, which was planned to take place in Porto, Portugal. Due to the COVID-19 pandemic the conference was held online during April 26-28, 2021. The 35 papers included in this book were carefully reviewed and selected from 113 submissions. The papers were organized in topical sections named: modeling with neural networks; modeling with statistical learning; modeling language and graphs; and modeling special data formats.

Intelligent Data Engineering and Automated Learning IDEAL 2020

Intelligent Data Engineering and Automated Learning     IDEAL 2020
  • Author : Cesar Analide,Paulo Novais,David Camacho,Hujun Yin
  • Publisher : Springer
  • Release : 30 October 2020
GET THIS BOOK Intelligent Data Engineering and Automated Learning IDEAL 2020

This two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.* The 93 papers presented were carefully reviewed and selected from 134 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2020 include big data challenges, machine learning, data mining, information retrieval and

Intelligent Data Analysis for Real Life Applications Theory and Practice

Intelligent Data Analysis for Real Life Applications  Theory and Practice
  • Author : Magdalena-Benedito, Rafael
  • Publisher : IGI Global
  • Release : 30 June 2012
GET THIS BOOK Intelligent Data Analysis for Real Life Applications Theory and Practice

With the recent and enormous increase in the amount of available data sets of all kinds, applying effective and efficient techniques for analyzing and extracting information from that data has become a crucial task. Intelligent Data Analysis for Real-Life Applications: Theory and Practice investigates the application of Intelligent Data Analysis (IDA) to these data sets through the design and development of algorithms and techniques to extract knowledge from databases. This pivotal reference explores practical applications of IDA, and it is