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Data Analysis and Knowledge Discovery  2022, Vol. 6 Issue (4): 130-138    DOI: 10.11925/infotech.2096-3467.2019.0893
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Reviewing Metaphor Research Based on Keyword Extraction Algorithm
Zhang Dongyu1,Gu Feng1,Cui Zijuan2,Hu Shaoxiang1,Zhang Wei1,Lin Hongfei3()
1School of Software, Dalian University of Technology, Dalian 116620, China
2International Office, Dalian University of Technology, Dalian 116024, China
3School of Computer Science and Technology, Dalian University of Technology, Dalian 116023, China
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Abstract  

[Objective] This paper reviews the developments of metaphor research in China in the past 40 years, aiming to provide references for linguists and then narrow the gaps between Chinese and foreign researchers. [Methods] First, we used keywords extraction algorithms to map metaphor documents into keyword sets. Then, we chose effective features as parameters for the regression models, which helped us predict the frequency of trending words in the next year. Finally, we analyzed the developments of metaphor research diachronically and synchronously. [Results] Our study compared the results of five regression models. Among them, the GBR model with the best fitting degree had the highest prediction accuracy for next year’s trending words. The feature ablation experiment also confirmed that our selected features were effective. [Limitations] The accuracy of keyword extraction algorithm could be optimized. [Conclusions] Metaphor research is developing towards the direction of cross-domains and inter-disciplines. The method of feature selection provides more references for research in prediction models.
Key words： Metaphor      Trend Prediction      Regression Model      Diachronic Analysis      Synchronic Analysis     
Received: 30 July 2019      Published: 12 May 2022
ZTFLH:  TP393  
Fund:Liaoning Province Social Science Planning Fund Project(L20BYY023)
Corresponding Authors: Lin Hongfei,ORCID： 0000-0003-0872-7688     E-mail: hflin@dlut.edu.cn
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Dongyu Zhang
Feng Gu
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Hongfei Lin

Cite this article:

Zhang Dongyu, Gu Feng, Cui Zijuan, Hu Shaoxiang, Zhang Wei, Lin Hongfei. Reviewing Metaphor Research Based on Keyword Extraction Algorithm. Data Analysis and Knowledge Discovery, 2022, 6(4): 130-138.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2019.0893     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2022/V6/I4/130

摘要 候选关键词 文章关键词
特别是在词汇多义研究领域,认知语言学致力于......概念隐喻理论......英语教师的教学策略......[19]。 隐喻;语言;教学;词汇 原则性多义网络;英语介词;中国英语学习者;习得
根据弗雷德里克·詹姆逊的看法,文学文本是......利用家庭关系作为社会秩序的隐喻......在空间流动中面对诱惑......具有特殊的象征功能[20]。 隐喻;空间;功能;文学 乔纳森·弗兰岑;伦理责任;新教伦理;自由市场
他精辟地指出......“不合身的长袍”的隐喻.......喻义层面看.......现实政治是所指[21]。 隐喻;意义;政治;分析 伊格尔顿;《麦克白》; 名分;能指;所指
由于中外在语言、思维以及文化之间存在诸多差异......通过字词结构和音韵的组合......探讨小说中蕴含的民间信仰以及文化隐喻的翻译[22]。 隐喻;小说;结构;思维 法译;格非;《人面桃花》;古典性
纳博科夫在转喻与隐喻的强烈对比中展示着故乡的美好与现今的漂泊感[23]。 隐喻;转喻;诗歌;对比 纳博科夫;爱情;自我意识
Examples of Articles with Keyword Comparisons
特征 特征说明
F1 候选关键词t在第i年作为关键词的频数
F2 候选关键词t在第i年出现在文档摘要中的频数
F3 候选关键词t截止到第i年出现过的存在年限
F4 候选关键词t在第i年中新作者的论文提及数
F5 候选关键词t在第i年中的重点基金论文提及数
F6 候选关键词t在第i年中期刊提及数
Key Features of Metaphor Research Trends
模型 MAE R2决定系数
LR 14.785 0.790
DTR 9.862 0.909
KNR 8.711 0.938
RFR 8.072 0.952
GBR 7.803 0.964
Experimental Results of Different Regression Models
特征选择 MAE R2决定系数
Baseline 8.735 0.859
Baseline+F3 8.247 0.913
Baseline+F3+F4 7.959 0.894
Baseline+F3+F4+F5 8.091 0.950
Baseline+F3+F4+F5+F6 7.803 0.964
Feature Ablation Experiment Results
Top-1 Metaphor
Top-13 Novel
Top-43 Sentiment
Top-75 Corpus
Change Trend Collection of Top5-35 Candidate Keyword F1 Features Over Time
Synchronic Analysis of Metaphorical Hotspots
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