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A comprehensive survey of artificial intelligence techniques for talent analytics
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 …
organizations to rethink how to make talent-related decisions in a quantitative manner …
Collaboration-aware hybrid learning for knowledge development prediction
In recent years, the rise of online Knowledge Management Systems (KMSs) has significantly
improved work efficiency in enterprises. Knowledge development prediction, as a critical …
improved work efficiency in enterprises. Knowledge development prediction, as a critical …
Job-sdf: A multi-granularity dataset for job skill demand forecasting and benchmarking
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 …
policymakers and businesses to anticipate and adapt to changes, ensuring that workforce …
Enhancing question answering for enterprise knowledge bases using large language models
Efficient knowledge management plays a pivotal role in augmenting both the operational
efficiency and the innovative capacity of businesses and organizations. By indexing …
efficiency and the innovative capacity of businesses and organizations. By indexing …
Market-aware Long-term Job Skill Recommendation with Explainable Deep Reinforcement Learning
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 …
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
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 …
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
Occupational skill demand (OSD) forecasting seeks to predict dynamic skill demand specific
to occupations, beneficial for employees and employers to grasp occupational nature and …
to occupations, beneficial for employees and employers to grasp occupational nature and …
Afdgcf: Adaptive feature de-correlation graph collaborative filtering for recommendations
Collaborative filtering methods based on graph neural networks (GNNs) have witnessed
significant success in recommender systems (RS), capitalizing on their ability to capture …
significant success in recommender systems (RS), capitalizing on their ability to capture …
[PDF][PDF] DGCD: an adaptive denoising GNN for group-level cognitive diagnosis
Group-level cognitive diagnosis, pivotal in intelligent education, aims to effectively assess
grouplevel knowledge proficiency by modeling the learning behaviors of individuals within …
grouplevel knowledge proficiency by modeling the learning behaviors of individuals within …
Towards efficient resume understanding: A multi-granularity multi-modal pre-training approach
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 …
widely acknowledged as a fundamental and crucial task, which aims to extract structured …