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 …

The role of noncoding RNAs in Parkinson's disease: biomarkers and associations with pathogenic pathways

MC Kuo, SCH Liu, YF Hsu, RM Wu - Journal of biomedical science, 2021 - Springer
The discovery of various noncoding RNAs (ncRNAs) and their biological implications is a
growing area in cell biology. Increasing evidence has revealed canonical and noncanonical …

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 …

Embracing artificial intelligence in the labour market: the case of statistics

J Liu, K Chen, W Lyu - Humanities and Social Sciences …, 2024 - nature.com
In an era marked by rapid advancements in artificial intelligence (AI), the dynamics of the
labour market are undergoing significant transformation. A common concern amidst these …

Nanopore sequencing reveals endogenous NMD-targeted isoforms in human cells

ED Karousis, F Gypas, M Zavolan, O Mühlemann - Genome biology, 2021 - Springer
Background Nonsense-mediated mRNA decay (NMD) is a eukaryotic, translation-
dependent degradation pathway that targets mRNAs with premature termination codons and …

Skill requirements in job advertisements: A comparison of skill-categorization methods based on wage regressions

Z Ao, G Horváth, C Sheng, Y Song, Y Sun - Information Processing & …, 2023 - Elsevier
In this paper, we compare different methods to extract skill demand from the text of job
descriptions. We propose the fraction of wage variation explained by the extracted skills as a …

Market-aware Long-term Job Skill Recommendation with Explainable Deep Reinforcement Learning

Y Sun, Y Ji, H Zhu, F Zhuang, Q He… - ACM Transactions on …, 2024 - dl.acm.org
Continuously learning new skills is essential for talents to gain a competitive advantage in
the labor market. Despite extensive efforts on relevance-or preference-based skill …

Rigl: A unified reciprocal approach for tracing the independent and group learning processes

X Yu, C Qin, D Shen, S Yang, H Ma, H Zhu… - Proceedings of the 30th …, 2024 - dl.acm.org
In the realm of education, both independent learning and group learning are esteemed as
the most classic paradigms. The former allows learners to self-direct their studies, while the …

[PDF][PDF] Pre-dygae: Pre-training enhanced dynamic graph autoencoder for occupational skill demand forecasting

X Chen, C Qin, Z Wang, Y Cheng, C Wang… - Proceedings of the 33th …, 2024 - ijcai.org
Occupational skill demand (OSD) forecasting seeks to predict dynamic skill demand specific
to occupations, beneficial for employees and employers to grasp occupational nature and …

Intelligent career planning via stochastic subsampling reinforcement learning

P Guo, K **ao, Z Ye, H Zhu, W Zhu - Scientific reports, 2022 - nature.com
Career planning consists of a series of decisions that will significantly impact one's life.
However, current recommendation systems have serious limitations, including the lack of …