COVID-19-Related Scientific Literature Exploration: Short Survey and Comparative Study

被引：1

作者：

Adil, Bahaj ^{[1
]}

Lhazmir, Safae ^{[1
]}

Ghogho, Mounir ^{[1
,2
]}

Benbrahim, Houda ^{[3
]}

机构：

[1] Int Univ Rabat, TicLAB, Sala El Jadida 11103, Morocco

[2] Univ Leeds, Fac Engn, Leeds LS2 9JT, W Yorkshire, England

[3] Mohamed V Univ, ENSIAS, Rabat 11000, Morocco

来源：

BIOLOGY-BASEL | 2022年 / 11卷 / 08期

关键词：

COVID-19; exploratory search; machine learning; document retrieval;

D O I：

10.3390/biology11081221

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Simple Summary The COVID-19-related literature has known a surge since the beginning of the pandemic. This surge prompted the creation of multiple literature exploration systems to help automate the exploration of scientific articles. In this work, we survey multiple COVID-19 literature exploration systems by exploring their most discriminative characteristics, give general design principles for these systems, and describe some of their limitations. The urgency of the COVID-19 pandemic caused a surge in the related scientific literature. This surge made the manual exploration of scientific articles time-consuming and inefficient. Therefore, a range of exploratory search applications have been created to facilitate access to the available literature. In this survey, we give a short description of certain efforts in this direction and explore the different approaches that they used.

引用

页数：20