Titlebook: Web Information Systems and Applications; 20th International C Long Yuan,Shiyu Yang,Xiang Zhao Conference proceedings 2023 The Editor(s) (i

Silent-Ischemia

流眼泪

Exaggerate

X-ray Prohibited Items Recognition Based on Improved YOLOv5 problem of overlapping occlusion of multi-scale contraband. Experimental results in the real X-ray prohibited items dataset demonstrate that our model outperforms state-of-the-art methods in terms of detection accuracy.

半球

菊花

Temporal Convolution and Multi-Attention Jointly Enhanced Electricity Load Forecastingssign different weight values to each timestep. We validate the effectiveness of our method using three real datasets. The results show that our model performs excellent results compared to traditional deep learning models.

Narcissist

Temporal Convolution and Multi-Attention Jointly Enhanced Electricity Load Forecastingssign different weight values to each timestep. We validate the effectiveness of our method using three real datasets. The results show that our model performs excellent results compared to traditional deep learning models.

CHANT

Rule-Enhanced Evolutional Dual Graph Convolutional Network for Temporal Knowledge Graph Link Predictlutional network is employed to capture the structural dependency of relations and the temporal dependency across adjacent snapshots. We conduct experiments on four real-world datasets. The results demonstrate that our model outperforms the baselines, and enhancing information in snapshots is benefi

iodides

Rule-Enhanced Evolutional Dual Graph Convolutional Network for Temporal Knowledge Graph Link Predictlutional network is employed to capture the structural dependency of relations and the temporal dependency across adjacent snapshots. We conduct experiments on four real-world datasets. The results demonstrate that our model outperforms the baselines, and enhancing information in snapshots is benefi

绝食

DINE: Dynamic Information Network Embedding for Social Recommendation users and items simultaneously and integrate the representations in dynamic and static information networks. In addition, the multi-head self-attention mechanism is employed to model the evolution patterns of dynamic information networks from multiple perspectives. We conduct extensive experiments

Toxoid-Vaccines