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 …

Collaboration-aware hybrid learning for knowledge development prediction

L Chen, C Qin, Y Sun, X Song, T Xu, H Zhu… - Proceedings of the ACM …, 2024‏ - dl.acm.org
In recent years, the rise of online Knowledge Management Systems (KMSs) has significantly
improved work efficiency in enterprises. Knowledge development prediction, as a critical …

Job-sdf: A multi-granularity dataset for job skill demand forecasting and benchmarking

X Chen, C Qin, C Fang, C Wang… - Advances in …, 2025‏ - proceedings.neurips.cc
In a rapidly evolving job market, skill demand forecasting is crucial as it enables
policymakers and businesses to anticipate and adapt to changes, ensuring that workforce …

Enhancing question answering for enterprise knowledge bases using large language models

F Jiang, C Qin, K Yao, C Fang, F Zhuang, H Zhu… - … on Database Systems …, 2024‏ - Springer
Efficient knowledge management plays a pivotal role in augmenting both the operational
efficiency and the innovative capacity of businesses and organizations. By indexing …

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 …, 2025‏ - 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 …

Afdgcf: Adaptive feature de-correlation graph collaborative filtering for recommendations

W Wu, C Wang, D Shen, C Qin, L Chen… - Proceedings of the 47th …, 2024‏ - dl.acm.org
Collaborative filtering methods based on graph neural networks (GNNs) have witnessed
significant success in recommender systems (RS), capitalizing on their ability to capture …

[PDF][PDF] DGCD: an adaptive denoising GNN for group-level cognitive diagnosis

H Ma, S Song, C Qin, X Yu, L Zhang, X Zhang… - The 33rd International …, 2024‏ - ijcai.org
Group-level cognitive diagnosis, pivotal in intelligent education, aims to effectively assess
grouplevel knowledge proficiency by modeling the learning behaviors of individuals within …

Towards efficient resume understanding: A multi-granularity multi-modal pre-training approach

F Jiang, C Qin, J Zhang, K Yao, X Chen… - … on Multimedia and …, 2024‏ - ieeexplore.ieee.org
In the contemporary era of widespread online recruitment, resume understanding has been
widely acknowledged as a fundamental and crucial task, which aims to extract structured …