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DOI: 10.14569/IJACSA.2022.0130404
PDF

Research on Intelligent Natural Language Texts Classification

Author 1: Chen Xiao Yu
Author 2: Zhang Xiao Min

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 4, 2022.

  • Abstract and Keywords
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Abstract: Natural language texts widely exist in many aspects of social life, and classification is of great significance to its efficient use and normalized preservation. Manual texts classification has the problems such as labor intensive, experience dependent and error prone, therefore, the research on intelligent classification of natural language texts has great social value. In recent years, machine learning technology has developed rapidly, and related researchers have carried out a lot of works on the texts classification based on machine learning, the research methods show the characteristic of diversification. This paper summarizes and compares the texts classification methods mainly from three aspects, including technical routes, text vectorization methods and classification information processing methods, in order to provide references for further research and explore the development direction of the texts classification.

Keywords: Machine learning; natural language texts; text vectorization; classification information processing

Chen Xiao Yu and Zhang Xiao Min, “Research on Intelligent Natural Language Texts Classification” International Journal of Advanced Computer Science and Applications(IJACSA), 13(4), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130404

@article{Yu2022,
title = {Research on Intelligent Natural Language Texts Classification},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130404},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130404},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {4},
author = {Chen Xiao Yu and Zhang Xiao Min}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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