Application of Big Data, Blockchain, and Internet of Things for Education Informatization: 4th EAI International Conference, BigIoT-EDU 2024, Beihai, China, August 18–20, 2024, Proceedings, Part V

Author:   Bouziane Brik ,  Shah Nazir
Publisher:   Springer Nature Switzerland AG
ISBN:  

9783032186331


Pages:   127
Publication Date:   02 May 2026
Format:   Paperback
Availability:   Not yet available   Availability explained
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Application of Big Data, Blockchain, and Internet of Things for Education Informatization: 4th EAI International Conference, BigIoT-EDU 2024, Beihai, China, August 18–20, 2024, Proceedings, Part V


Overview

The five-volume set LNICST 658-662 constitutes the proceedings of the 4th EAI International Conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2024, held in Beihai, China, during August 18–20, 2024.  The 271 full papers included in these volumes were carefully reviewed and selected from 669 submissions. They are organized in the following topical sections:  Part I: Application of Data Mining in Intelligence Education; Application of Ant Colony Algorithms in Intelligence Education; Application of Apriori Algorithm in Intelligence Education; and  Application of K-means clustering algorithm in intelligence education. Part II: Application of K-means clustering algorithm in intelligence education; Application of Big Data in Intelligence Education; The Application of Computer in Intelligence Education; and Application of Model in Intelligence Education. Part III: Application of Model in Intelligence Education; Application of Virtual Technology in Intelligence Education; Application of Network Platform in Intelligence Education; and The Application of Machine Learning in Intelligence Education. Part IV: The Application of Machine Learning in Intelligence Education; Deep learning in Intelligence Education; Clouding Computing and blockchain in Intelligence Education; and Other intelligent algorithms in Intelligence Education. Part V: Other intelligent algorithms in Intelligence Education.

Full Product Details

Author:   Bouziane Brik ,  Shah Nazir
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
ISBN:  

9783032186331


ISBN 10:   3032186331
Pages:   127
Publication Date:   02 May 2026
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Forthcoming
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

.- Other intelligent algorithms in Intelligence Education. .- The Application of Decision Tree Algorithm in the Employment Analysis of College Graduates. .- Teaching Resource Storage Management and Its Search Algorithm Based on Grid Algorithm. .- Optimal allocation of innovation and entrepreneurship education resources in colleges and universities based on PSO algorithm. .- Health management evaluation algorithm for college students based on distributed multi-agent system. .- Employment analysis and prediction of higher vocational students based on decision tree classification algorithm. .- Data analysis of teaching management in higher vocational colleges based on decision tree algorithm. .- Application of Depth-First Search Algorithm in Teaching Quality Monitoring and Management System of Colleges and Universities. .- Analysis of the rational application of college English teaching to situation construction under association rule mining algorithm. .- An Improved ID3 Algorithm and Its Application in University Public Physical Education. .-  Adaptive learning recommendation algorithm for vocational education under the background of artificial intelligence. .- Analysis of the optimization algorithm in the thought of art education and the development direction of image AI. .- Analysis on the rational application of English teaching in college construction under the correlation rule mining algorithm.

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