A Design of Content-based Metric Learning Model for HR Matching

인재매칭을 위한 내용기반 척도학습모형의 설계

  • Song, Hee Seok (Department of Global IT Business in Hannam University)
  • Received : 2020.11.10
  • Accepted : 2020.12.04
  • Published : 2020.12.31


The job mismatch between job seekers and SMEs is becoming more and more intensifying with the serious difficulties in youth employment. In this study, a bi-directional content-based metric learning model is proposed to recommend suitable jobs for job seekers and suitable job seekers for SMEs, respectively. The proposed model not only enables bi-directional recommendation, but also enables HR matching without relearning for new job seekers and new job offers. As a result of the experiment, the proposed model showed superior performance in terms of precision, recall, and f1 than the existing collaborative filtering model named NCF+GMF. The proposed model is also confirmed that it is an evolutionary model that improves performance as training data increases.



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