College Writing Research Trend Analysis and Improvement Plan : Focusing on Academic Journals from 2001 to 2020

2021 ◽  
Vol 93 ◽  
pp. 247-285
Author(s):  
Hyeon-jeong Kim
Keyword(s):  
Trend Analysis ◽  
College Writing ◽  
Research Trend ◽  
Academic Journals ◽  
Improvement Plan ◽  
Writing Research

scholarly journals Cancer Research Trend Analysis Based on Fusion Feature Representation

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 338
Author(s):  
Jingqiao Wu ◽  
Xiaoyue Feng ◽  
Renchu Guan ◽  
Yanchun Liang
Keyword(s):  
Cancer Research ◽  
Trend Analysis ◽  
Research Trends ◽  
Feature Representation ◽  
Research Trend ◽  
Good Representation ◽  
Text Representation ◽  
Classical Text ◽  
Representation Model ◽  
Text Feature

Machine learning models can automatically discover biomedical research trends and promote the dissemination of information and knowledge. Text feature representation is a critical and challenging task in natural language processing. Most methods of text feature representation are based on word representation. A good representation can capture semantic and structural information. In this paper, two fusion algorithms are proposed, namely, the Tr-W2v and Ti-W2v algorithms. They are based on the classical text feature representation model and consider the importance of words. The results show that the effectiveness of the two fusion text representation models is better than the classical text representation model, and the results based on the Tr-W2v algorithm are the best. Furthermore, based on the Tr-W2v algorithm, trend analyses of cancer research are conducted, including correlation analysis, keyword trend analysis, and improved keyword trend analysis. The discovery of the research trends and the evolution of hotspots for cancers can help doctors and biological researchers collect information and provide guidance for further research.

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