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The job vacancy use case has been chosen as the initial focus area for investigation. Following a survey of the literature in December 2020, an experiment was conducted using web-scraped Australian job advertisements data from Seek, which are publicly available on the Kaggle data science portal. The motivation for this work is to create entity-level data about jobs that can be utilised in the ABS Labour Market Analysis Project (LMAP) to deliver new insights on the impact of COVID-19 on employment and labour demand. This project also uses GLIDE – an advanced knowledge discovery system under development by the ABS.
The Seek dataset required manual annotation to create training data for the machine learning process. The Python package spaCy was then used to generate a basic NER language model to extract key job characteristics. The next stage of research aims to develop a machine-interpretable concept model of job classes, and to iteratively improve the performance of the language models for use in the LMAP.
For further information, please contact Phil Newbold at email@example.com.
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1504.0 - Methodological News, Mar 2021
Latest ISSUE Released at 11:30 AM (CANBERRA TIME) 29/03/2021