NKOS Workshop
The programme is still being finalized and is subject to ongoing updates as sessions are scheduled. Please check back regularly for the latest changes.
Capturing Semantic Gaps in MeSH through Human-AI Collaboration
Authors: Jian Qin, Bei Yu, Qiaoyi Liu
This study aims to explore ways for keeping KOS current with advances in scientific research and to experiment the effectiveness of human-AI collaboration in detecting and identifying topical specific semantic gaps in MeSH as a proof of concept. Using a dataset on public health policy and COVID-19 vaccines, the experiment found one-third papers have no author keywords and among those author keywords are available, there is a low proportion of overlaps between MeSH headings and author keywords. Further analysis identified structural mismatches and conceptual gaps between MeSH and author keywords and discussed the factors that contributed to these problems. The use of AI tools in this preliminary study provides useful insights for future larger scale KOS evaluation.
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Jian Qin
Syracuse University
Jian Qin is Professor of the iSchool at Syracuse University and currently serves as the Director for Dublin Core Academy. She conducts research in metadata, knowledge organization and representation, data and knowledge modeling, ontologies, research collaboration networks, research impact assessment, and data curation. Her research has received funding from U.S. National Science Foundation, U.S. National Institutes for Health, and U.S. Institute for Museum and Library Services. She was the recipient of the 2020 Frederick G. Kilgour Award for Research in Library and Information Technology.
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