Titlebook: Database Systems for Advanced Applications. DASFAA 2021 International Workshops; BDQM, GDMA, MLDLDSA, Christian S. Jensen,Ee-Peng Lim,Chih-

傲慢人

An Attention-Based Approach to Rule Learning in Large Knowledge Graphsn the attention mechanism. The attention-based sampling is designed to reduce the search space of rule extraction and thus to improve efficiency of rule learning for a given target predicate. An implementation ARL (Attention-based Rule Learner) of rule learning for KGs is obtained by combining the n

竊喜

Multi-scale Gated Inpainting Network with Patch-Wise Spacial Attentionoduce fuzzy textures and distorted structures due to ignoring the semantic relevance and feature continuity of the holes region. To address this challenge, we propose a detailed depth generation model (GS-Net) equipped with a Multi-Scale Gated Holes Feature Inpainting module (MG) and a Patch-wise Sp

arbovirus

哄騙

Nonthreatening

Surface Defect Detection Method of Hot Rolling Strip Based on Improved SSD Modelbining attention mechanism and multi-feature fusion network was proposed. In this method, the traditional SSD model was used as the basic framework, and the ResNet50 network after knowledge distillation was selected as the feature extraction network. The low-level features and high-level features we

調(diào)味品

變化無常

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水槽

Jill Cheeseman,Christiane Benz,Yianna Pullens significantly improved the trajectory compression rate, and its average time complexity and space complexity is .(.) and .(1) respectively. Finally, we conducted experiments on three real data sets to verify that the ROPW algorithm performed very well in terms of compression rate and time efficien

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