11 citations · 20 across the 8 of their papers we have counts for
8 papers
A Survey on GNN-based Link Prediction: Techniques, Applications, and Challenges
Chengcheng Sun, Yajie Song, Cheng Zhai +6
Graph Neural Networks (GNNs) have emerged as the leading paradigm for link prediction, enabling the inference of missing connections and the anticipation of potential future links.…
Knowledge Graphs Meet Graph Neural Networks: A Comprehensive Survey
Chengcheng Sun, Jiayun Tian, Cheng Zhai +5
Graph Neural Networks (GNNs) have emerged as a powerful paradigm in Knowledge Graphs (KGs) due to their intrinsic ability to model graph-structured data. However, there remains a l…
A Survey of AIOps in the Era of Large Language Models
Lingzhe Zhang, Tong Jia, Mengxi Jia +7
As large language models (LLMs) grow increasingly sophisticated and pervasive, their application to various Artificial Intelligence for IT Operations (AIOps) tasks has garnered sig…
A Gravity-informed Spatiotemporal Transformer for Human Activity Intensity Prediction
Yi Wang, Zhenghong Wang, Fan Zhang +9
Human activity intensity prediction is crucial to many location-based services. Despite tremendous progress in modeling dynamics of human activity, most existing methods overlook p…
Data clustering: a fundamental method in data science and management
Tai Dinh, Wong Hauchi, Daniil Lisik +4
This paper explores the critical role of data clustering in data science, emphasizing its methodologies, tools, and diverse applications. Traditional techniques, such as partitiona…
Unique Security and Privacy Threats of Large Language Models: A Comprehensive Survey
Shang Wang, Tianqing Zhu, Bo Liu +4
With the rapid development of artificial intelligence, large language models (LLMs) have made remarkable advancements in natural language processing. These models are trained on va…
Bayes-enhanced Multi-view Attention Networks for Robust POI Recommendation
Jiangnan Xia, Yu Yang, Senzhang Wang +3
POI recommendation is practically important to facilitate various Location-Based Social Network services, and has attracted rising research attention recently. Existing works gener…
Uncertainty-guided Boundary Learning for Imbalanced Social Event Detection
Jiaqian Ren, Hao Peng, Lei Jiang +4
Real-world social events typically exhibit a severe class-imbalance distribution, which makes the trained detection model encounter a serious generalization challenge. Most studies…