Efforts towards understanding the structure and development of scientific domain through text mining

Corridor with double doors with digital coding covering walls and ceiling
Public lectures / seminars

Thursday 13 January 2022

02:00 PM - 04:00 PM

Location

Coventry University and Online

Cost

Free

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Overview

This event forms part of the Centre for Computational Science and Mathematical Modelling's spotlight series. 

Abstract

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.