Skip to main content
SpringerLink
Log in

Automatic Classification and Sharing of Teaching Resources in English Online Teaching System Based on SVM

  • Conference paper
  • First Online:
e-Learning, e-Education, and Online Training (eLEOT 2023)

  • 38 Accesses

Abstract

In order to improve the classification and sharing performance of teaching resources, an automatic classification and sharing method of teaching resources in online English teaching system based on SVM is proposed. According to learners’ demands for teaching resources, the tasks and objectives of online English teaching are determined, and the content performance characteristics of teaching resources are given through the digital integration of teaching resources in the online English teaching system. Based on learners’ internal psychological activity process and cognitive rules, a feature extraction model of teaching resources is constructed to extract the features of English teaching resources. According to the optimal classification plane of support vector machine, the nonlinear classification problem of teaching resource features is transformed into a quadratic optimization problem, and the Gaussian kernel function is selected as the kernel function of support vector machine to classify the features of English teaching resources. By calculating the weighted vector of English teaching resources, English teaching resources are cleaned, and the continuous sliding window distance of English teaching resources attribute compression is given by using attribute compression. Combined with the spatial trajectory function of quantitative coding, the characteristics of English teaching resources are quantified and coded. Combined with the design of teaching resource sharing algorithm, the automatic classification and sharing of teaching resources in online English teaching system is realized. The experimental results show that the proposed method can improve the utilization rate of teaching resources, reduce the sharing delay and improve the classification and sharing performance of teaching resources, no matter with or without manual intervention. Therefore, it shows that this method can improve the classification and sharing effectiveness of English teaching resources.

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 64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 84.99
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. Liu, S., Dai, Y., Cai, Z., et al.: Construction of double-precision wisdom teaching framework based on blockchain technology in cloud platform. IEEE Access 9(2), 11823–11834 (2021)

    Article  Google Scholar 

  2. Tang, X.: Design of teaching resource sharing platform based on VEM framework. J. Jilin Univ. Inf. Sci. Edn. 40(2), 288–294 (2022)

    Google Scholar 

  3. Xiao, Q.: Design of sharing model of ideological and political teaching resources based on machine learning. Microcomput. Appl. 38(10), 28–31 (2022)

    MathSciNet  Google Scholar 

  4. Liang, X., Yin, J.: Recommendation algorithm for equilibrium of teaching resources in physical Education network based on trust relationship. J. Internet Technol. 23(1), 133–141 (2022)

    Article  Google Scholar 

  5. Bai, X.J., Li, J.J.: Applied research of knowledge in the field of artificial intelligence in the intelligent retrieval of teaching resources. Sci. Program. 30(4), 992–998 (2021)

    Google Scholar 

  6. Wang, Z., Muthu, B.A., Kadry, S.N.: Research on the design of analytical communication and information model for teaching resources with cloud: haring platform. Comput. Appl. Eng. Educ. 29(2), 359–369 (2021)

    Article  Google Scholar 

  7. Zhao, G., Ding, J.: Image network teaching resource retrieval algorithm based on deep hash algorithm. Sci. Program. 32(8), 968–978 (2021)

    Google Scholar 

  8. Yang, X.: Research on integration method of AI teaching resources based on learning behavior data analysis. Int. J. Contin. Eng. Educ. Life-Long Learn. 30(4), 492–508 (2020)

    Google Scholar 

  9. Zhang, Y., Wang, D.: Integration model of English teaching resources based on artificial intelligence. Int. J. Contin. Eng. Educ. Life-Long Learn. 30(4), 398–405 (2020)

    Google Scholar 

  10. Huajian, W., Zhifeng, W.: Design of simulation teaching system based on modular production and processing. Comput. Simul. 39(04), 205–209 (2022)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Public Foundation Courses, Wuhan Institute of Design and Sciences, Wuhan, 430000, China

    Dan Zhao

  2. Medical School of Jinshan Branch, Affiliated to Shanghai University of Medicine and Health Sciences, Shanghai, 200237, China

    Hui Dong

Authors
  1. Dan Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hui Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dan Zhao .

Editor information

Editors and Affiliations

  1. Nanjing University of Posts and Telecommunications, Nanjing, China

    Guan Gui

  2. Yantai University, Yantai, China

    Ying Li

  3. Institute of High Performance Computing, Fusionopolis, Singapore

    Yun Lin

Rights and permissions

Reprints and permissions

Copyright information

© 2024 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

Zhao, D., Dong, H. (2024). Automatic Classification and Sharing of Teaching Resources in English Online Teaching System Based on SVM. In: Gui, G., Li, Y., Lin, Y. (eds) e-Learning, e-Education, and Online Training. eLEOT 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 544. Springer, Cham. https://doi.org/10.1007/978-3-031-51468-5_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-51468-5_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-51467-8

  • Online ISBN: 978-3-031-51468-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation