Improving Data Extraction System to Parse Data from Scraped Job Advertisements

Authors

  • Claudia Nathasia Jason Petra Christian University

DOI:

https://doi.org/10.9744/jirae.5.1.19-22

Keywords:

data parsing, job advertisement, data segmentation, data classification, feature extraction

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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Published

2021-08-26

Issue

Section

Articles