Syntax-Based Skill Extractor for Job Advertisements

Ellery Smith, Martín Braschler, Andreas Weiler, Thomas Haberthuer · 2019

In the context of extracting relevant skill-terms from job advertisements, we propose a syntax-based method for generating large amounts of machine-labelled text from a small amount of human-labelled data. This is then used to solve the vocabulary problem and significantly increase recall when detecting skills.

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