HarriGT: Linking news articles to scientific literature

被引:0
|
作者
Ravenscroft, James [1 ,3 ,4 ]
Clare, Amanda [2 ]
Liakata, Maria [1 ,3 ]
机构
[1] Univ Warwick, Ctr Sci Comp, Coventry CV4 7AL, W Midlands, England
[2] Aberystwyth Univ, Dept Comp Sci, Aberystwyth SY23 3DB, Dyfed, Wales
[3] Alan Turing Inst, 96 Euston Rd, London NW1 2DBB, England
[4] Filament AI, CargoWorks, 1-2 Hatfields, London SE1 9PG, England
基金
英国工程与自然科学研究理事会;
关键词
IMPACT;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Being able to reliably link scientific works to the newspaper articles that discuss them could provide a breakthrough in the way we rationalise and measure the impact of science on our society. Linking these articles is challenging because the language used in the two domains is very different, and the gathering of online resources to align the two is a substantial information retrieval endeavour. We present HarriGT, a semi-automated tool for building corpora of news articles linked to the scientific papers that they discuss. Our aim is to facilitate future development of information-retrieval tools for newspaper/scientific work citation linking. HarriGT retrieves newspaper articles from an archive containing 17 years of UK web content. It also integrates with 3 large external citation networks, leveraging named entity extraction, and document classification to surface relevant examples of scientific literature to the user. We also provide a tuned candidate ranking algorithm to highlight potential links between scientific papers and newspaper articles to the user, in order of likelihood. HarriGT is provided as an open source tool (http://harrigt.xyz).
引用
收藏
页码:19 / 24
页数:6
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