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|Title:||Understanding talent flux - analysing job posts to understand economic activities||Authors:||Beh, Wei Siang||Keywords:||DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing||Issue Date:||2018||Abstract:||In Singapore, several online job portals provide a service for interested job applicants by hosting employer posted job advertisements. Although users of these services could perform a job query with a keyword search and optional additional filters, the only statistic that they could access off the portal was the total sum of applicable search results from the query. As various invaluable data could be extracted off information provided by the job posts, the lack in data analysis and visualization tools limits the potential of resources provided by online job portals. This FYP project’s primary objective was to provide a solution to this limitation by proposing to implement several data analysis techniques for eventual data visualization, using processed data from job postings crawled off STJobs, an online job portal, as the base dataset for the analysis techniques. Implemented on a front-end web application, the data visualization was displayed in the form of various interactive charts, based on different elements found in the original advertisements. Based off the visualization results, numerous inferences were provided by the author to make sense of each observation identified. Although the visualizations implemented encompassed of multiple elements from the original job posts, the author envisions room for growth as there are still numerous other techniques that could be performed onto the data collected. If implementation is continued, the tool would empower job seekers, employers and policy-makers to gain vital insights into the Singapore’s job market and employment trends.||URI:||http://hdl.handle.net/10356/73932||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SCSE Student Reports (FYP/IA/PA/PI)|
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