A comprehensive survey of artificial intelligence techniques for talent analytics

C Qin, L Zhang, Y Cheng, R Zha, D Shen… - arXiv preprint arXiv …, 2023 - arxiv.org
In today's competitive and fast-evolving business environment, it is a critical time for
organizations to rethink how to make talent-related decisions in a quantitative manner …

Job recommender systems: A review

C De Ruijt, S Bhulai - arXiv preprint arXiv:2111.13576, 2021 - arxiv.org
This paper provides a review of the job recommender system (JRS) literature published in
the past decade (2011-2021). Compared to previous literature reviews, we put more …

Enhancing job recommendation through llm-based generative adversarial networks

Y Du, D Luo, R Yan, X Wang, H Liu, H Zhu… - Proceedings of the …, 2024 - ojs.aaai.org
Recommending suitable jobs to users is a critical task in online recruitment platforms. While
existing job recommendation methods encounter challenges such as the low quality of …

Recruitpro: A pretrained language model with skill-aware prompt learning for intelligent recruitment

C Fang, C Qin, Q Zhang, K Yao, J Zhang… - Proceedings of the 29th …, 2023 - dl.acm.org
Recent years have witnessed the rapid development of machine-learning-based intelligent
recruitment services. Along this line, a large number of emerging models have been …

Modeling two-way selection preference for person-job fit

C Yang, Y Hou, Y Song, T Zhang, JR Wen… - Proceedings of the 16th …, 2022 - dl.acm.org
Person-job fit is the core technique of online recruitment platforms, which can improve the
efficiency of recruitment by accurately matching the job positions with the job seekers …

Learning to match jobs with resumes from sparse interaction data using multi-view co-teaching network

S Bian, X Chen, WX Zhao, K Zhou, Y Hou… - Proceedings of the 29th …, 2020 - dl.acm.org
With the ever-increasing growth of online recruitment data, job-resume matching has
become an important task to automatically match jobs with suitable resumes. This task is …

Knowledge enhanced person-job fit for talent recruitment

K Yao, J Zhang, C Qin, P Wang, H Zhu… - 2022 IEEE 38th …, 2022 - ieeexplore.ieee.org
As an essential task of talent recruitment, person-job fit aims to measure the matching
degree between talent qualifi-cation and the job requirements of a position. Existing studies …

Learning effective representations for person-job fit by feature fusion

J Jiang, S Ye, W Wang, J Xu, X Luo - Proceedings of the 29th ACM …, 2020 - dl.acm.org
Person-job fit is to match candidates and job posts on online recruitment platforms using
machine learning algorithms. The effectiveness of matching algorithms heavily depends on …

A challenge-based survey of e-recruitment recommendation systems

Y Mashayekhi, N Li, B Kang, J Lijffijt… - ACM Computing Surveys, 2024 - dl.acm.org
E-recruitment recommendation systems recommend jobs to job seekers and job seekers to
recruiters. The recommendations are generated based on the suitability of job seekers for …

Exploring Internal and External Interactions for Semi‐Structured Multivariate Attributes in Job‐Resume Matching

T Shao, C Song, J Zheng, F Cai… - International Journal of …, 2023 - Wiley Online Library
Job‐resume matching (JRM) is the core of online recruitment services for predicting the
matching degree between a job post and a resume. Most of the existing methods for JRM …