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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 2
468-473,478

Improved Chinese short text classification method for low frequency words

Luo Xiaoboa
Lin Jiayub
Liang Zuhonga
Wang Zhanga
a. School of Computer Science & Technology, b. Library, Guangdong University of Technology, Guangzhou 510006, China
DOI: 10.19734/j.issn.1001-3695.2021.08.0385

Abstract

A large number of low-frequency words existed in Chinese short text classification, reasonable development and utilization could effectively improve the effect of text classification. Aiming at the problem that low-frequency words couldn't be effectively used in the research of text classification based on word vector, this paper proposed a method of data enhancement based on low-frequency words. Firstly, it used the data generated by the restricted text generation model to fine tune the word vector of low-frequency words, and then used a word vector construction algorithm to transfer the updated information of high-frequency words to low-frequency words, so that low-frequency words could obtain a more accurate word vector representation that conformed to the distribution of training set. Secondly, it introduced prior knowledge such as similar words and entity concepts to supplement context information. Finally, it used the improved Chi-square statistics to remove the obvious noise words, and designed the word attention layer to weight each word to reduce the impact of irrelevant noise on classification. Experiments on several basic classification models show that each basic model has been significantly improved after applying the improved method. It not only shows the effectiveness of the proposed method, but also shows that low-frequency words can improve the classification effect in short text classification task.

Foundation Support

国家自然科学基金资助项目(71402033)
广东省图书馆科研课题(GDTK1928)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.08.0385
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 2
Section: Algorithm Research & Explore
Pages: 468-473,478
Serial Number: 1001-3695(2022)02-024-0468-06

Publish History

[2021-12-17] Accepted Paper
[2022-02-05] Printed Article

Cite This Article

罗孝波, 林佳瑜, 梁祖红, 等. 针对低频词进行改进的中文短文本分类方法 [J]. 计算机应用研究, 2022, 39 (2): 468-473,478. (Luo Xiaobo, Lin Jiayu, Liang Zuhong, et al. Improved Chinese short text classification method for low frequency words [J]. Application Research of Computers, 2022, 39 (2): 468-473,478. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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