• Àüü
  • ÀüÀÚ/Àü±â
  • Åë½Å
  • ÄÄÇ»ÅÍ
´Ý±â

»çÀÌÆ®¸Ê

Loading..

Please wait....

¿µ¹® ³í¹®Áö

Ȩ Ȩ > ¿¬±¸¹®Çå > ¿µ¹® ³í¹®Áö > TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)

TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) Hot Keyword Extraction of Sci-tech Periodicals Based on the Improved BERT Model
¿µ¹®Á¦¸ñ(English Title) Hot Keyword Extraction of Sci-tech Periodicals Based on the Improved BERT Model
ÀúÀÚ(Author) Bing Liu   Zhijun Lv   Nan Zhu   Dongyu Chang   Mengxin Lu  
¿ø¹®¼ö·Ïó(Citation) VOL 16 NO. 06 PP. 1800 ~ 1817 (2022. 06)
Çѱ۳»¿ë
(Korean Abstract)
¿µ¹®³»¿ë
(English Abstract)
With the development of the economy and the improvement of living standards, the hot issues in the subject area have become the main research direction, and the mining of the hot issues in the subject currently has problems such as a large amount of data and a complex algorithm structure. Therefore, in response to this problem, this study proposes a method for extracting hot keywords in scientific journals based on the improved BERT model.It can also provide reference for researchers,and the research method improves the overall similarity measure of the ensemble,introducing compound keyword word density, combining word segmentation, word sense set distance, and density clustering to construct an improved BERT framework, establish a composite keyword heat analysis model based on I-BERT framework.Taking the 14420 articles published in 21 kinds of social science management periodicals collected by CNKI(China National Knowledge Infrastructure) in 2017-2019 as the experimental data, the superiority of the proposed method is verified by the data of word spacing, class spacing, extraction accuracy and recall of hot keywords. In the experimental process of this research, it can be found that the method proposed in this paper has a higher accuracy than other methods in extracting hot keywords, which can ensure the timeliness and accuracy of scientific journals in capturing hot topics in the discipline, and finally pass Use information technology to master popular key words.
Å°¿öµå(Keyword) Bidirectional encoder   hot keyword   representations from transformers (bert)   sci-tech periodicals   similarity measurement  
ÆÄÀÏ÷ºÎ PDF ´Ù¿î·Îµå