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This slide explains the feature engineering strategy used in our system.
First, skills are represented in a way that captures the relevance between candidate competencies and job requirements.
Second, educational qualification, specifically the degree, is incorporated to align a candidate¡¯s academic background with role expectations.
Third, age is included as a normalized feature and is used as a contextual signal rather than a strict filtering criterion.
Finally, work experience is encoded to quantify professional exposure and career progression, allowing the model to distinguish between different career stages. |
IEEE/ICACT20260013 Slide.08
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