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Titlebook: Big Data and Social Computing; 7th China National C Xiaofeng Meng,Qi Xuan,Zi-Ke Zhang Conference proceedings 2022 The Editor(s) (if applica

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发表于 2025-3-21 19:01:36 | 显示全部楼层 |阅读模式
期刊全称Big Data and Social Computing
期刊简称7th China National C
影响因子2023Xiaofeng Meng,Qi Xuan,Zi-Ke Zhang
视频video
学科分类Communications in Computer and Information Science
图书封面Titlebook: Big Data and Social Computing; 7th China National C Xiaofeng Meng,Qi Xuan,Zi-Ke Zhang Conference proceedings 2022 The Editor(s) (if applica
影响因子This book constitutes refereed proceedings of the 7th China National Conference on Big Data and Social Computing, BDSC 2022, held in Hangzhou, China, from August 11-13, 2022.The 24 full papers and 2 short papers presented in this volume were carefully reviewed and selected from a total of 99 submissions. The papers in the volume are organised according to the following topical headings: urban computing and social governance; artificial intelligence and cognitive science; social network and group behavior; digital society and public security; digital government and public big data.
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The Effects of Intervention Strategies for COVID-19 Transmission Control on Campus Activity is critical to understand the transmission risk of COVID-19 under various scenario, especially during public health emergency. Taking the Tsinghua university’s anniversary as a representative case, a set of prevention and control strategies are established and investigated. In the case study, an al
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Prediction of Female Fertility Structure and Population Change in China by Modified SIR Modelountries. In recent years, China, where family planning is implemented, has also gradually shown such a trend. The decline of fertility rate limits the further development of the society. In this paper, based on the SIR infectious disease model, we improve the SIR fertility structure model applicabl
发表于 2025-3-22 11:16:45 | 显示全部楼层
Generative Adversarial Network for Imputation of Road Network Traffic State Dataffic data, a novel generative adversarial network for the imputation of road network traffic data is proposed in this paper, i.e., GAE-GAN-LSTM. The spatiotemporal characteristics were extracted using a improved graph auto-encoder (GAE), followed by a generative adversarial network (GAN) to generate
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A Secured Deep Reinforcement Learning Model Based on Vertical Federated Learning learning. In this work, a secured DRL based on vertical federated learning (VFL), named VF-DRL, is proposed to protect the model’s information. Specifically, in the proposed VF-DRL, each client trains a partial local model, and uploads the feature embedding cooperatively to a server for global mode
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