Research on Educational Data Mining Based on Big Data
Educational data mining (EDM) is a cross-disciplinary technology involving computer science, education, statistics, etc. It analyzes and mines education-related data to discover and solve various types of education problems. To make them better understand
- PDF / 18,941,329 Bytes
- 362 Pages / 439.37 x 666.142 pts Page_size
- 5 Downloads / 249 Views
40
e-Learning, e-Education, and Online Training 6th EAI International Conference, eLEOT 2020 Changsha, China, June 20–21, 2020 Proceedings, Part II
Part 2
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Editorial Board Members Ozgur Akan Middle East Technical University, Ankara, Turkey Paolo Bellavista University of Bologna, Bologna, Italy Jiannong Cao Hong Kong Polytechnic University, Hong Kong, China Geoffrey Coulson Lancaster University, Lancaster, UK Falko Dressler University of Erlangen, Erlangen, Germany Domenico Ferrari Università Cattolica Piacenza, Piacenza, Italy Mario Gerla UCLA, Los Angeles, USA Hisashi Kobayashi Princeton University, Princeton, USA Sergio Palazzo University of Catania, Catania, Italy Sartaj Sahni University of Florida, Gainesville, USA Xuemin (Sherman) Shen University of Waterloo, Waterloo, Canada Mircea Stan University of Virginia, Charlottesville, USA Xiaohua Jia City University of Hong Kong, Kowloon, Hong Kong Albert Y. Zomaya University of Sydney, Sydney, Australia
340
More information about this series at http://www.springer.com/series/8197
Shuai Liu Guanglu Sun Weina Fu (Eds.) •
•
e-Learning, e-Education, and Online Training 6th EAI International Conference, eLEOT 2020 Changsha, China, June 20–21, 2020 Proceedings, Part II
123
Editors Shuai Liu Human Normal University Changsha, China
Guanglu Sun Harbin University Harbin, China
Weina Fu Hunan Normal University Changsha, China
ISSN 1867-8211 ISSN 1867-822X (electronic) Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN 978-3-030-63954-9 ISBN 978-3-030-63955-6 (eBook) https://doi.org/10.1007/978-3-030-63955-6 © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affil
Data Loading...
