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 - researchr publication

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Mesut Kaya, Toine Bogers, David Graus, Sepideh Mesbah, Chris Johnson 0011, Francisco Gutiérrez, editors, 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. Volume 3218 of CEUR Workshop Proceedings, CEUR-WS.org, 2022. [doi]

Conference: hr-recsys2022

Abstract is missing.

Automated Personnel Scheduling with Reinforcement Learning and Graph Neural NetworksBenjamin Platten, Matthew Macfarlane, David Graus, Sepideh Mesbah. [doi]

Flexible Job Classification with Zero-Shot LearningThom Lake. [doi]

Skill Extraction from Job Postings using Weak SupervisionMike Zhang, Kristian Nørgaard Jensen, Rob van der Goot, Barbara Plank. [doi]

Using vector representations for matching tasks to skillsMiriam Amin, Jan-Peter Bergmann, Yuri Campbell. [doi]

Design of Negative Sampling Strategies for Distantly Supervised Skill ExtractionJens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder, Thomas Demeester. [doi]

Model Threshold Optimization for Segmented Job-Jobseeker Recommendation SystemYichao Jin, Anirudh Alampally, Dheeraj Toshniwal, Zhiming Xu, Ankush Girdhar. [doi]

Closing the Gender Wage Gap: Adversarial Fairness in Job RecommendationClara Rus, Jeffrey Luppes, Harrie Oosterhuis, Gido H. Schoenmacker. [doi]

Beyond human-in-the-loop: scaling occupation taxonomy at IndeedSuyi Tu, Olivia Cannon. [doi]

Explainable Career Path Predictions using Neural ModelsRoan Schellingerhout, Volodymyr Medentsiy, Maarten Marx. [doi]

DGL4C: a Deep Semi-supervised Graph Representation Learning Model for Resume ClassificationWissem Inoubli, Armelle Brun. [doi]

End-to-End Bias Mitigation in Candidate Recommender Systems with Fairness GatesAdam Mehdi Arafan, David Graus, Fernando P. Santos, Emma Beauxis-Aussalet. [doi]

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