| Vol-3218 urn:nbn:de:0074-3218-4 Copyright © 2022 for the individual papers by the papers' authors. Copyright © 2022 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# RecSys-in-HR 2022
Recommender Systems for Human Resources 2022

### 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.

Edited by

### Mesut Kaya *
Toine Bogers *
David Graus **
Sepideh Mesbah **
Chris Johnson ***
Francisco Gutiérrez ****

* Aalborg University Copenhagen, Department of Communication and Psychology, Faculty of Humanities, Copenhagen, Denmark
** Randstad, Randstad Groep Nederland, Diemen, The Netherlands
*** Indeed, Indeed, USA
**** KU Leuven, Department of Computer Science, Leuven, Belgium

## Table of Contents

- Summary: There were 12 papers submitted for peer-review to this workshop. Out of these, 11 papers were accepted for this volume, 11 as regular papers.

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

2022-09-16: submitted by Mesut Kaya, metadata incl. bibliographic data published under Creative Commons CC0
2022-09-19: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|