Research on Automatic Scoring Algorithm of Chinese Subjective Questions Based on Text Mining

Abstract:

At present, the research on automatic evaluation of computer online examination system has become a hot issue. Natural language processing technology based on text mining has unique advantages in text similarity calculation. This paper designs the TR-BFS-WE-WMD integrated algorithm for automatic review of Chinese subjective questions based on text mining, uses the word database to integrate the BFS algorithm, realizes the calculation of the text full sentence similarity and keyword matching, and solves the problem of text semantic similarity. Experimental results prove that this algorithm has good accuracy and effectiveness. The TR-BFS-WE-WMD algorithm provides a useful attempt for the intelligent research of the computer automatic review system and has good practical value.

• Periodical: Advances in Science and Technology (Volume 105)
• Pages: 377-383
• DOI: https://doi.org/10.4028/www.scientific.net/AST.105.377
• Online since: April 2021
• Authors: Bo Yang*, Yu Qi Yao
• Keywords: Automatic Review, Chinese Subjective Questions, Text Similarity, Text Mining, Word Vector

References

[1] Jiang Zhenfeng and Liu Li 2013 Research on Automatic Evaluation of Subjective Questions Based on Computer Aided Evaluation[J]. Journal of Chongqing Normal University: Natural Science Edition. 30(2)74-78. [In Chinese].

[2] Zhao Zhihong, Han Yongguo. Research on automatic evaluation system of subjective questions based on NLP-TF technology [J]. Software Guide. 2013, 01: 82-83.

[3] Chen Yile. Research on automatic scoring technology of Chinese composition based on regression analysis [D]. Harbin Institute of Technology, (2016).

[4] Chu Shangwu. Automatic scoring algorithm for subjective questions based on LDA topic model [D]. Xiangtan University, (2017).

[5] Li Nana and Liu Peiyu 2019 Automatic summarization optimization algorithm based on TextRank [J]. Application Research of Computers. 36(4)25-36. [In Chinese].

[6] Gao Sidan and Yuan Chunfeng 2004 Research on computer automatic correction technology of subjective examination questions[J]. Computer Application Research. 21(2)181-185.

[7] Sun Haixia and Qian Qing 2010 A review of research on semantic similarity calculation methods based on ontology[J]. Data Analysis and Knowledge Discovery. 26(1)51–56. [In Chinese].

[8] Crossley and Scott A 2019 The Tool for the Automatic Analysis of Cohesion 2.0: Integrating semantic similarity and text overlap[J]. Behavior Research Methods. 51(1)14-27.

DOI: 10.3758/s13428-018-1142-4

[9] Chapelle C A and Chung Y R2010The promise of NLP and speech processing technologies in language assessment[J]. Language Testing. 27(3)301-315.

DOI: 10.1177/0265532210364405