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Data Analysis and Knowledge Discovery
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A review of recent studies on literature-based discovery
Dai Bing,Hu Zhengyin
(Chengdu Library and Information Center, Chinese Academy of Sciences, Chengdu 610041, China)
(Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)
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[Objective] This paper investigates the literatures of literature-based discovery (LBD) in the recent ten years, which will help the researchers better understand the new research progress, development trend and challenges on this topic. [Coverage] Using "literature based discovery", "literature and knowledge discovery" in Chinese and English to search in the databases of web of science, CNKI and Baidu academic, the publication year is limited from 2010 to 2020, and 72 representative literatures are selected for review. [Methods] Firstly, this paper summarized the literatures from four aspects: research objects, methods and techniques, result evaluation and typical applications, and after that the future development trend and challenges of LBD are summarized. [Results] The research objects of LBD tend to be more complicated, the analysis methods and techniques tend to be more intelligent, the discovery results are more enriched, and more LBD applications appear. LBD also faces some challenges in multi-source heterogeneous data fusion, interpretability of knowledge discovery, effectiveness evaluation of results, and collaboration of multi-disciplinary experts. [Limitations] This paper mainly reviews the recent development of LBD based on literatures, and it is not enough to cover the LBD tools or systems and industry applications. [Conclusions] As an interdisciplinary research field of information science, informatics and data science, LBD is of great significance for mining interdisciplinary knowledge and providing high-quality subject knowledge services. However, there are still some challenges to support potential scientific discoveries.

Key words Literature-based discovery      Literature mining      Knowledge discovery      Knowledge graph      Information research      
Published: 21 December 2020
ZTFLH:  TP393,G250  

Cite this article:

Dai Bing, Hu Zhengyin. A review of recent studies on literature-based discovery . Data Analysis and Knowledge Discovery, 0, (): 1-.

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