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Improving data extraction system to parse data from scraped job advertisements

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.

Creator(s)
  • (26415134) CLAUDIA NATHASIA JASON
Contributor(s)
  • Henry Novianus Palit, S.Kom → Advisor and Examination Committee
Publisher
Universitas Kristen Petra; 2020
Language
English
Category
s1 – Undergraduate Thesis
Sub Category
Skripsi/Undergraduate Thesis
Source
Undergraduate Thesis No. 02021918/INF/2019; Claudia Nathasia Jason (26415134)
Subject(s)
  • DATA MANAGEMENT
File(s)

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