Skip to main content
SpringerLink
Log in

Big Data Automatic Classification Processing System Based on Cloud Computing

  • Conference paper
  • First Online:
Tenth International Conference on Applications and Techniques in Cyber Intelligence (ICATCI 2022) (ICATCI 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 170))

  • 416 Accesses

Abstract

How to quickly, accurately and fully obtain the information we need from social media, and how to effectively organize and manage this information are major challenges facing the current information technology space. Considering the needs of experimental research and practical application, this paper makes a detailed modular design of the automatic text classification processing system based on semantic Chinese. In terms of the impact of keyword weights on specific categories, the original algorithm is improved by introducing two parameters: the ratio of keywords to all keywords contained in the current category, and the average number of samples in this category compared to the current category. Number of samples. According to the principle of combining category concepts, the weights between keywords and categories are combined and calculated, and the highest weighted sorting number is obtained as the optimal sorting number of the text to be sorted. The final test results show that the improved algorithm has certain advantages compared with other algorithms in terms of recall rate, precision rate, F1 value, macro average and micro average. The macro-average precision, recall and FI of the improved algorithm are 4–5 percentage points higher than those of the other two algorithms.

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 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
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

Similar content being viewed by others

References

  1. Demir, F., Sobahi, N., Siuly, S., et al.: Exploring deep learning features for automatic classification of human emotion using EEG rhythms. IEEE Sens. J. 21, 14923–14930 (2021)

    Article  Google Scholar 

  2. Mihandoost, S., Azimzadeh, E.: Introducing an efficient statistical model for automatic modulation classification. J. Signal Process. Syst. 92(1), 123–134 (2019). https://doi.org/10.1007/s11265-019-01458-5

    Article  Google Scholar 

  3. Huang, L., He, X., Fang, L., et al.: Automatic classification of retinal optical coherence tomography images with layer guided convolutional neural network. IEEE Signal Process. Lett. 26, 1026–1030 (2019)

    Article  Google Scholar 

  4. Hussain Hassan, N.M., Nashat, A.A.: New effective techniques for automatic detection and classification of external olive fruits defects based on image processing techniques. Multidimension. Syst. Signal Process. 30(2), 571–589 (2018). https://doi.org/10.1007/s11045-018-0573-5

    Article  MATH  Google Scholar 

  5. Li, C., Li, W.: Automatic classification algorithm for multisearch data association rules in wireless networks. Wirel. Commun. Mob. Comput. 2021(1), 1–9 (2021)

    Article  Google Scholar 

  6. Borwankar, R., Ludwig, R.: An optical surface inspection and automatic classification technique using the rotated wavelet transform. IEEE Trans. Instrum. Meas. 67, 690–697 (2018)

    Article  Google Scholar 

  7. Sevik, U., Karakullukcu, E., Berber, T., et al.: Automatic classification of skin burn colour images using texture-based feature extraction. Image Process. IET 13(11), 2018–2028 (2019)

    Article  Google Scholar 

  8. Eken, S., Menhour, H., Koksal, K.: DoCA: a content-based automatic classification system over digital documents. IEEE Access 7(99), 97996–98004 (2019)

    Article  Google Scholar 

  9. Alharbi, M., Alhuseini, A., Ragheb, A., et al.: Automatic modulation classification: investigation for millimeter wave over fiber channels. IEEE Photonics Technol. Lett. 31(13), 1092–1095 (2019)

    Article  Google Scholar 

  10. Baghdadi, Y., Bourree, A., Robert, A., et al.: Automatic classification of free-text medical causes from death certificates for reactive mortality surveillance in France. Int. J. Med. Inform. 131(Nov.), 103915.1–103915.8 (2019)

    Google Scholar 

  11. Luque, A., Romero-Lemos, J., Carrasco, A., et al.: Non-sequential automatic classification of anuran sounds for the estimation of climate-change indicators. Expert Syst. Appl. 95(APR.), 248–260 (2018)

    Google Scholar 

  12. Ponchard, C., Demolin, D., Hassid, S.: Automatic classification of French stops consonants. J. Acoust. Soc. Am. 146(4), 3084–3085 (2019)

    Article  Google Scholar 

Download references

Acknowledgment

Jiangxi Province Educational Science Planning Project (No. 19YB266).

Author information

Authors and Affiliations

  1. Jiangxi University of Software Professional Technology, Nanchang, Jiangxi, China

    Jun Li

  2. Jawaharlal Nehru University, New Delhi, India

    Ankit Singh

Authors
  1. Jun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ankit Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jun Li .

Editor information

Editors and Affiliations

  1. Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, VIC, Australia

    Jemal H. Abawajy

  2. School of Computer Engineering and Sciences, Shanghai Polytechnic University, Shanghai, China

    Zheng Xu

  3. School of Computer Science, University of Oklahoma, Norman, OK, USA

    Mohammed Atiquzzaman

  4. Department of Information Systems and Cyber Security, The University of Texas at San Antonio, San Antonio, TX, USA

    Xiaolu Zhang

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Li, J., Singh, A. (2023). Big Data Automatic Classification Processing System Based on Cloud Computing. In: Abawajy, J.H., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) Tenth International Conference on Applications and Techniques in Cyber Intelligence (ICATCI 2022). ICATCI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 170. Springer, Cham. https://doi.org/10.1007/978-3-031-29097-8_36

Download citation

Publish with us

Policies and ethics

Search

Navigation