Handbook of Educational Data Mining

von

Romero, CristobalHrsg.Ventura, SebastianHrsg.Pechenizkiy, MykolaHrsg.Baker, Ryan S.J.d.Hrsg.

BuchGebunden

Verkaufsrang23470in

CHF206.00

BuchCHF206.00

E-BookabCHF87.05

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Beschreibung

Educational data mining (EDM) is an emerging discipline concerned with developing methods for exploring the different types of data that come from an educational context. This book presents the applications of data mining techniques in education.

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Details

ISBN/GTIN978-1-4398-0457-5

ProduktartBuch

EinbandGebunden

VerlagTaylor and FrancisCRC Press

Erscheinungsdatum25.10.2010

Auflage1. A.

ReiheChapman & Hall/CRC Data Mining and Knowledge Discovery Series

Seiten535 Seiten

SpracheEnglisch

MasseBreite 178 mm, Höhe 254 mm

Gewicht1088 g

IllustrationenFarb., s/w. Abb.

Artikel-Nr.3640000

KatalogBuchzentrum

Datenquelle-Nr.17705958

Weitere Details

Reihe

Computational Methods of Feature Selection

Understanding Complex Datasets

Knowledge Discovery for Counterterrorism and Law Enforcement

Multimedia Data Mining

Constrained Clustering

Information Discovery on Electronic Health Records

Data Mining for Design and Marketing

Geographic Data Mining and Knowledge Discovery

The Top Ten Algorithms in Data Mining

Text Mining

Biological Data Mining

Statistical Data Mining Using SAS Applications

Knowledge Discovery from Data Streams

Handbook of Educational Data Mining

Mining Software Specifications

Spectral Feature Selection for Data Mining

Music Data Mining

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Advances in Machine Learning and Data Mining for Astronomy

Support Vector Machines

Contrast Data Mining

Data Clustering

RapidMiner

Computational Business Analytics

Computational Intelligent Data Analysis for Sustainable Development

Data Classification

Graph-Based Social Media Analysis

Event Mining

Accelerating Discovery

Healthcare Data Analytics

Text Mining and Visualization

Advances in Machine Learning and Data Mining for Astronomy

Data Mining with R

Data Science and Analytics with Python

Large-Scale Machine Learning in the Earth Sciences

Data Science and Analytics with Python

Social Networks with Rich Edge Semantics

Data Mining for Design and Marketing

Mining Software Specifications

Biological Data Mining

Autor

Romero, CristobalHrsg.Ventura, SebastianHrsg.Pechenizkiy, MykolaHrsg.Baker, Ryan S.J.d.Hrsg.

Cristóbal Romero is an associate professor in the Department of Computer Science at the University of Córdoba in Spain. Dr. Romero is a member of the International Working Group on Educational Data Mining and was conference co-chair of the Second International Conference on Educational Data Mining. His research interests include the application of artificial intelligence and data mining techniques to education and e-learning systems.Sebastián Ventura is an associate professor in the Department of Computer Science at the University of Córdoba in Spain. Dr. Ventura has been a reviewer for User Modelling and User Adapted Interaction, Information Sciences, and Soft Computing and was conference co-chair of the Second International Conference on Educational Data Mining. His research interests encompass machine learning, data mining, and their applications as well as the application of KDD techniques to e-learning.Mykola Pechenizkiy is an assistant professor in the Department of Computer Science at Eindhoven University of Technology in the Netherlands. Dr. Pechenizkiy has been involved in the organization of workshops, special tracks, and conferences on applications of data mining in medicine, industry, and education. He is conference co-chair of the Fourth International Conference on Educational Data Mining. His research is focused on knowledge discovery, data mining, machine learning, and their applications.Ryan Baker is an assistant professor of psychology and the learning sciences in the Department of Social Science and Policy Studies, with a collaborative appointment in computer science, at Worcester Polytechnic Institute in Massachusetts. An associate editor of the Journal of Educational Data Mining, Dr. Baker was program co-chair of the First International Conference on Educational Data Mining and conference chair of the Third International Conference on Educational Data Mining. His research is at the intersection of educational data mining, machine learning, human-computer interaction, and educational psychology.