3 papers
cs.LG2024
Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks
Jianjun Wei, Yue Liu, Xin Huang +3
This paper explores the applications and challenges of graph neural networks (GNNs) in processing complex graph data brought about by the rapid development of the Internet. Given t…
cs.IR2024
A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining
Wenyi Liu, Rui Wang, Yuanshuai Luo +3
With the explosive growth of Internet data, users are facing the problem of information overload, which makes it a challenge to efficiently obtain the required resources. Recommend…
cs.LG2024
Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining
Xu Yan, Yaoting Jiang, Wenyi Liu +2
This paper introduces a novel spatiotemporal feature representation model designed to address the limitations of traditional methods in multidimensional time series (MTS) analysis.…