Titlebook: Intelligent Information Processing XII; 13th IFIP TC 12 Inte Zhongzhi Shi,Jim Torresen,Shengxiang Yang Conference proceedings 2024 IFIP Int

故意

Dual Contrastive Learning for?Anomaly Detection in?Attributed Networksarget node. Accordingly, our method designs two types of contrastive instance pairs to fully exploit the structural and attribute information for detecting anomalous nodes at different levels regarding two focused consistencies. This approach is more effective in detecting anomalies and mitigating t

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Table Orientation Classification Model Based on BERT and TCSMNent. Additionally, it proposes an improved Temporal Convolutional Network (TCN) named Temporal Convolutional Sparse Multilayer Perceptron Network (TCSMN). This network captures sequential structural features of cells and their surrounding neighbors, enhancing the ability to extract semantic features