Efforts towards understanding the structure and development of scientific domain through text mining
Thursday 13 January 2022
02:00 PM - 04:00 PM
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This event forms part of the Centre for Computational Science and Mathematical Modelling's spotlight series.
The exponential growth of scientific publications makes it more difficult than ever before for scientists to keep up-to-date with the most recent scientific development. AI techniques, especially text mining technologies, are crucial for extracting useful knowledge from scientific publications, from individual papers to a scientific topic such as (e.g. machine translation or text summarisation), or even a scientific domain (e.g. natural language processing or artificial intelligence). From the STEM education point of view, scholarly text mining also has high potential in downstream applications for both HE educators (e.g. mining actionable knowledge from STEM education literature) or postgraduate students (e.g. building a mind map for a scientific topic). At the same time, the scientific community also faces severe challenges in quality peer review, which is especially significant reflected in the peer review processes (including IJCAI2020). The three speakers will share their work towards this end and viewpoints about scholarly text mining from different aspects: contextualised citation network analysis, text mining for open science, and ontology and knowledge graph construction.