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Titlebook: Big Data and Social Computing; 9th China National C Xiaofeng Meng,Zhidong Cao,Xiu-Xiu Zhan Conference proceedings 2024 The Editor(s) (if ap

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41#
發(fā)表于 2025-3-28 15:26:46 | 只看該作者
42#
發(fā)表于 2025-3-28 21:21:28 | 只看該作者
,Hei?wasser- und Dampfheizungen, dark web. Most security protection software and probes are designed for identifying unencrypted traffic, and they cannot effectively classify encrypted traffic from the dark web due to its unique anonymity. Existing methods do not comprehensively consider the external statistical features and the i
43#
發(fā)表于 2025-3-29 01:33:59 | 只看該作者
Big Data and Social Computing978-981-97-5803-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
44#
發(fā)表于 2025-3-29 03:25:35 | 只看該作者
45#
發(fā)表于 2025-3-29 10:09:44 | 只看該作者
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發(fā)表于 2025-3-29 11:59:25 | 只看該作者
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發(fā)表于 2025-3-29 19:04:56 | 只看該作者
EG-ConMix: An Intrusion Detection Method Based on?Graph Contrastive Learning incorporate contrastive learning to discern the difference between normal and malicious traffic samples, facilitating the extraction of key features. Thorough experiments conducted on two publicly accessible datasets reveal that EG-ConMix surpasses current state-of-the-art methods in intrusion dete
48#
發(fā)表于 2025-3-29 23:13:01 | 只看該作者
49#
發(fā)表于 2025-3-30 02:48:23 | 只看該作者
Mapping Gridded Wealth Index Using Open Geospatial Data in Zambiasing open geospatial data. The results indicated that the proxy features derived from open geospatial data were able to obtain an . value of 0.78 on the test set in WI prediction in Zambia. Meanwhile, the variable importance metrics highlight that the top 5 high contribution variables are derived fr
50#
發(fā)表于 2025-3-30 07:33:08 | 只看該作者
Bidirectional Multi-grain Graph Convolution Network for?Origin-Destination Demand Predictionhnique that leverages dual-scale convolutional layers to extract pertinent demand information. The integration of a graph convolution network and a global temporal correlation module within BiDP enables the capture of broader spatiotemporal dependencies, thereby refining the prediction process. Comp
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