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All Journal International Journal of Industrial Research and Applied Engineering
Claudia Nathasia Jason
Petra Christian University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Improving Data Extraction System to Parse Data from Scraped Job Advertisements Claudia Nathasia Jason
International Journal of Industrial Research and Applied Engineering Vol 5, No 1: APRIL 2020
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jirae.5.1.19-22

Abstract

Extracting the information from an online job advertisement might be a little tricky. The information is wrapped with redundant information, called boilerplate, that is not related to the job at all. The information also needs to be segmented and classified into the right class or groups. After the information has been classified, it is easier to find the features (e.g., required skills and required education) that make the later processing faster.
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