Skip to main content
SpringerLink
Log in

Research on Large Data Mining for Online Education of Mobile Terminal Based on Block Chain Technology

  • Conference paper
  • First Online:
Advanced Hybrid Information Processing (ADHIP 2022)

Included in the following conference series:

  • 304 Accesses

Abstract

In order to manage the massive online instructional resources effectively and realize the goal of quickly mining massive instructional resources, this paper proposes a research method of online instructional large data mining based on block chain technology. Based on the block chain technology, this paper constructs the recognition model of online education of mobile terminal, optimizes the management system of big data of online education of mobile terminal. Experimental results show that the block chain-based mobile terminal online education large data mining method has high practicability in the practical application, and fully meets the research requirements.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Jin, Y., Chen, H.: Value orientations, realistic limitations and effective strategies of big data mining for education. Theory Pract. Educ. 41(19), 3–8 (2021)

    Google Scholar 

  2. Zhang, T., Zhang, S.: Research on design and computing of learner model of educational big data mining. E-educ. Res. 41(09), 61–67 (2020)

    Google Scholar 

  3. Xu, J., Zhang, G.: Application and practice of data mining algorithms based on apriori. Comput. Technol. Develop. 30(4), 206–210 (2020)

    Google Scholar 

  4. Liu, W., Li, X.: Research on terminal online education data mining technology based on model driving. Modern Electronics Technique 43(16), 112–114+118 (2020)

    Google Scholar 

  5. Lian, J., Fang, S., Zhou, Y.: Model predictive control of the fuel cell cathode system based on state quantity estimation. Comput. Simulat. 37(07), 119–122 (2020)

    Google Scholar 

  6. Wang, D., Liu, H., Qiu, M.: Analysis method and application verification on teacher behavior data in smart classroom. China Educ. Technol. 05, 120–127 (2020)

    Google Scholar 

  7. Wang, C., Cheng, J., Sang, X., et al.: Data privacy-preserving for blockchain: State of the art and trends. J. Comput. Res. Develop. 58(10), 2099–2119 (2021)

    Google Scholar 

  8. Liu, F., Yang, J., Li, Z., et al.: A secure multi-party computation protocol for universal data privacy protection based on blockchain. J. Comput. Res. Develop. 58(02), 281–290 (2021)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Jiangxi Software Vocational and Technical University, Nanchang, 330041, China

    Zhitao Yu & Wei Zou

Authors
  1. Zhitao Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wei Zou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhitao Yu .

Editor information

Editors and Affiliations

  1. Hunan Normal University, Changsha, China

    Weina Fu

  2. Harbin Engineering University, Harbin, China

    Lin Yun

Rights and permissions

Reprints and permissions

Copyright information

© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yu, Z., Zou, W. (2023). Research on Large Data Mining for Online Education of Mobile Terminal Based on Block Chain Technology. In: Fu, W., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-28787-9_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-28787-9_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-28786-2

  • Online ISBN: 978-3-031-28787-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation