RECSYS-in-HR 2024
Recommender Systems for Human Resources 2024

Table of Contents

• Summary: There were 17 papers submitted for peer-review to this workshop. Out of these, 10 papers were accepted for this volume, 9 as regular papers. 1 as short paper.

• A Dynamic Jobs-Skills Knowledge Graph
  Alejandro Seif, Sarah Toh, Hwee Kuan Lee
• MELO: An Evaluation Benchmark for Multilingual Entity Linking of Occupations
  Federico Retyk, Luis Gascó, Casimiro Pio Carrino, Daniel Deniz, Rabih Zbib
• Combined Unsupervised and Contrastive Learning for Multilingual Job Recommendation
  Daniel Deniz, Federico Retyk, Laura García-Sardiña, Hermenegildo Fabregat, Luis Gasco, Rabih Zbib
• Parallel and Mini-Batch Stable Matching for Large-Scale Reciprocal Recommender Systems
  Kento Nakada, Kazuki Kawamura, Ryosuke Furukawa
• Enhancing Reliability in Recommendation Systems: Beyond point estimations to monitor population stability
  Yingshi Chen, Mohit Jain, Vaibhav Sawhney, Liyasi Wu
• Pseudo-online Measurement of Retrieval Recall for Job Recommendations - A case study at Indeed (short paper)
  Liyasi Wu, Yi Wei Pang, Warren Cai
• Creating Healthy Friction: Determining Stakeholder Requirements of Job Recommendation Explanations
  Roan Schellingerhout, Francesco Barile, Nava Tintarev
• Skill matching at scale: freelancer-project alignment for efficient multilingual candidate retrieval
  Warren Jouanneau, Marc Palyart, Emma Jouffroy
• Hardware-effective Approaches for Skill Extraction in Job Offers and Resumes
  Laura Vásquez-Rodríguez, Bertrand Audrin, Samuel Michel, Samuele Galli, Julneth Rogenhofer, Jacopo Negro Cusa, Lonneke van der Plas
• On the Biased Assessment of Expert Finding Systems
  Jens-Joris Decorte, Jeroen Van Hautte, Chris Develder, Thomas Demeester