Skip to main content

Semantic Retrieval Method of UK Education Resource Metadata in Hierarchical Cloud P2P Network

  • Conference paper
  • First Online:
  • 413 Accesses

Abstract

The traditional semantic retrieval method of British educational resource metadata has a low recall rate. Therefore, a semantic retrieval method of British educational resource metadata under a layered cloud peer-to-peer network is proposed. Preprocess the British education resource metadata and query and expand the semantics of the British education resource metadata. On this basis, the semantic correlation of the British education resource metadata is calculated to achieve the semantic retrieval of the British education resource metadata under the layered cloud peer-to-peer network. The experiment proves that the semantic retrieval method of the metadata of British education resources under the layered cloud peer-to-peer network designed this time has a higher recall rate than the traditional method and has practical application significance.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
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

Learn about institutional subscriptions

References

  1. Fan, Y.X., Guo, J.F., Lan, Y.Y., et al.: A context-aware deep sentence matching model. J. Chinese Inf. Process. 31(5), 156–162 (2017)

    Google Scholar 

  2. Chen, Q., Dai, Q.: Research and Application of Semantic Understanding Methods in Searching dvertising

    Google Scholar 

  3. Microcontrollers Embedded Syst. 19(6), 13–17 (2019)

    Google Scholar 

  4. Miao, T.P., Han, J.J., Wang, Z.J.: Inteligent semantic understanding of the morphological characteristics of chinese function words in search Engines. Qutlook Electron. Technol. 26(6), 52–55 (2019)

    Google Scholar 

  5. Zhang, S.W., Ouyang, C., Yang, X.H., et al.: Word semantic similarity computation based on integrating HowNet and search engines. J. Comput. Appl. 37(4), 1056–1060 (2017)

    Google Scholar 

  6. Sun, M.Y., Tian, X.D.: Similarity sorting method for retrieval results of linear algebra formula. Comput. Eng. 44(4), 253–261 (2018)

    Google Scholar 

  7. Zhang, Q.Y., Lin, M., Zhang, S.J.: Research on automatic construction of domain concepts on Wikipedia semantic knowledge base. Appl. Res. Comput. 35(1), 130–134 (2018)

    Google Scholar 

  8. Han, Y.Q.: The realization and mechanism of library subject collection semantization based on the entity-relationship mapping method of BIBFRAME model: take “information retrieval” as an example. Libr. J. 36(9), 35–41 (2017)

    Google Scholar 

  9. Feng, S.X., Zhang, Y.M.: Study on semantic retrieval to improve IT level of Northeastern Asian shipping center. Logistics Technol. 36(7), 150–153 (2017)

    Google Scholar 

  10. Wu, X., Zhou, D.: Personalized query expansion method based on multiple semantic relationships. Pattern Recogn. Artif. Intell. 30(11), 1039–1047 (2017)

    Google Scholar 

  11. He, Y., Li, T., Wang, W., et al.: A semantic similarity integration method for software feature location problem. J. Comput. Res. Dev. 56(2), 394–409 (2019)

    Google Scholar 

Download references

Funding

Special project to build mianyang normal university in 2019: Theoretical research and practical exploration of foreign language teacher education (project number: 2019 mysytdz11) college.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xia Wang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 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

Wang, X., Li, MJ. (2020). Semantic Retrieval Method of UK Education Resource Metadata in Hierarchical Cloud P2P Network. In: Liu, S., Sun, G., Fu, W. (eds) e-Learning, e-Education, and Online Training. eLEOT 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 340. Springer, Cham. https://doi.org/10.1007/978-3-030-63955-6_29

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-63955-6_29

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-63954-9

  • Online ISBN: 978-3-030-63955-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics