Application of Literature-Based Discovery in Nonmedical Disciplines: A Survey

被引:2
作者
Hui, Wendy [1 ,2 ]
Lau, Wai Kwong [3 ]
机构
[1] Lingnan Univ, Hong Kong, Peoples R China
[2] Curtin Univ, Perth, WA, Australia
[3] Univ Western Australia, Sch Math & Stat, Nedlands, WA, Australia
来源
2019 2ND INTERNATIONAL CONFERENCE ON COMPUTING AND BIG DATA (ICCBD 2019) | 2019年
关键词
Literature mining; Literature-based discovery; non-medical; KNOWLEDGE; RAYNAUDS;
D O I
10.1145/3366650.3366660
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The rapid increase in the academic literature has resulted in overspecialization of knowledge. To overcome this overspecialization, literature-based discovery (LBD) has been proposed to help discover promising and under-investigated hypotheses that connect two bodies of knowledge. The method has been around for more than 30 years, but its application has mostly been confined to the medical sciences. In this study, we perform a comprehensive survey of the literature on the application of LBD in nonmedical disciplines, summarize the approaches used, and discuss ways to promote the use of LBD in nonmedical disciplines.
引用
收藏
页码:7 / 11
页数:5
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