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ORCID2nd HR@RecSys 2022: Seattle, WA, USA
- Mesut Kaya, Toine Bogers, David Graus, Sepideh Mesbah, Chris Johnson, Francisco Gutiérrez:
Proceedings of the 2nd Workshop on Recommender Systems for Human Resources (RecSys-in-HR 2022) co-located with the 16th ACM Conference on Recommender Systems (RecSys 2022), Seattle, USA, 18th-23rd September 2022. CEUR Workshop Proceedings 3218, CEUR-WS.org 2022 - Benjamin Platten, Matthew Macfarlane, David Graus, Sepideh Mesbah:
Automated Personnel Scheduling with Reinforcement Learning and Graph Neural Networks. - Suyi Tu, Olivia Cannon:
Beyond human-in-the-loop: scaling occupation taxonomy at Indeed. - Clara Rus, Jeffrey Luppes, Harrie Oosterhuis, Gido H. Schoenmacker:
Closing the Gender Wage Gap: Adversarial Fairness in Job Recommendation. - Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder, Thomas Demeester:
Design of Negative Sampling Strategies for Distantly Supervised Skill Extraction. - Wissem Inoubli, Armelle Brun:
DGL4C: a Deep Semi-supervised Graph Representation Learning Model for Resume Classification. - Adam Mehdi Arafan, David Graus, Fernando P. Santos, Emma Beauxis-Aussalet:
End-to-End Bias Mitigation in Candidate Recommender Systems with Fairness Gates. - Roan Schellingerhout, Volodymyr Medentsiy, Maarten Marx:
Explainable Career Path Predictions using Neural Models. - Thom Lake:
Flexible Job Classification with Zero-Shot Learning. - Yichao Jin, Anirudh Alampally, Dheeraj Toshniwal, Zhiming Xu, Ankush Girdhar:
Model Threshold Optimization for Segmented Job-Jobseeker Recommendation System. - Mike Zhang, Kristian Nørgaard Jensen, Rob van der Goot, Barbara Plank:
Skill Extraction from Job Postings using Weak Supervision. - Miriam Amin, Jan-Peter Bergmann, Yuri Campbell:
Using vector representations for matching tasks to skills.
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