Journal article
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
P Brown, Y Zhou, AC Tan, MA El-Esawi, T Liehr, O Blanck, DP Gladue, GMF Almeida, T Cernava, CO Sorzano, AWK Yeung, MS Engel, AR Chandrasekaran, T Muth, MS Staege, SV Daulatabad, D Widera, J Zhang, A Meule, K Honjo Show all
Database | Published : 2019
Open access
Abstract
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contribut..
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Awarded by Medical Research Council
Funding Acknowledgements
Griffith University Gowonda HPC Cluster; Queensland Cyber Infrastructure Foundation