The Application of Natural Language Processing Technology in the Era of Big Data


  • Hao Yan Syracuse University
  • Jingxuan Xiao Georgia Institution of Technology
  • Beibei Zhang Xi'an Jiaotong University
  • Liziqiu Yang University of Illinois-Urbana Champaign
  • Ping Qu Maharishi International University



Natural Language Processing, Text Classification, Information Extraction, Question and Answer System, Machine Translation


Natural language processing technology plays an important role in the era of big data, provides a powerful support for data mining and information retrieval, this paper discusses the application of natural language processing technology in the big data environment, analyzes the text classification, information extraction, answer system and the application prospect of machine translation, and expounds the related technology in improving the efficiency and quality of data processing advantages, the research shows that natural language processing technology brings new opportunities for big data analysis, laid a foundation for realizing more intelligent data utilization.


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Author Biographies

Hao Yan, Syracuse University

Engineering and Computer Science, Syracuse University, Syracuse, NY, USA.

Jingxuan Xiao, Georgia Institution of Technology

Computer Science, Georgia Institution of Technology, Atlanta, GA, USA.

Beibei Zhang, Xi'an Jiaotong University

Software Engineering, Xi'an Jiaotong University, Xi'an, China.

Liziqiu Yang, University of Illinois-Urbana Champaign

Statistics and Computer Science, University of Illinois-Urbana Champaign, Champaign, IL, USA.

Ping Qu, Maharishi International University

Computer Science, Maharishi International University, Fairfield, IA, USA.


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	The Application of Natural Language Processing Technology in the Era of Big Data




How to Cite

H. Yan, J. Xiao, B. Zhang, L. Yang, and P. Qu, “The Application of Natural Language Processing Technology in the Era of Big Data”, Journal of Industrial Engineering & Applied Science, vol. 2, no. 3, pp. 20–27, Jun. 2024.




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