Accepted Papers (2022)

Model Threshold Optimization for Segmented Job-Jobseeker Recommendation System
Yichao Jin, Anirudh Alampally, Dheeraj Toshniwal, Zhiming Xu and Ankush Girdhar

End-to-End Bias Mitigation in Candidate Recommender Systems with Fairness Gates
Adam Mehdi Arafan, David Graus, Fernando Pascoal Santos and Emmanuelle Beauxis-Aussalet

Closing the Gender Wage Gap: Adversarial Fairness in Job Recommendation
Clara Rus, Jeffrey Luppes, Harrie Oosterhuis and Gido Schoenmacker

Explainable Career Path Predictions using Neural Models
Roan Schellingerhout, Volodymyr Medentsiy and Maarten Marx

Design of Negative Sampling Strategies for Distantly Supervised Skill Extraction
Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder and Thomas Demeester

Flexible Job Classification with Zero-Shot Learning
Thomas Lake

Skill Extraction from Job Postings using Weak Supervision
Mike Zhang, Kristian Nørgaard Jensen, Rob van der Goot and Barbara Plank

Using vector representations for matching tasks to skills
Miriam Amin, Jan-Peter Bergmann and Yuri Campbell

DGL4C: a Deep Semi-supervised Graph Representation Learning Model for Resume Classification
Wissem Inoubli and Armelle Brun

Beyond human-in-the-loop: scaling occupation taxonomy at Indeed
Suyi Tu and Olivia Cannon

Automated Personnel Scheduling with Reinforcement Learning and Graph Neural Networks
Ben Platten, Matthew Macfarlane, David Graus and Sepideh Mesbah