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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.
Program Studi Informatika
Universitas Kristen Petra
2020
English
S1
Undergraduate Thesis No. 02021918/INF/2019; Claudia Nathasia Jason (26415134)
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