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Titlebook: Big Data; 8th CCF Conference, Hong Mei,Weiguo Zhang,Li Wang Conference proceedings 2021 Springer Nature Singapore Pte Ltd. 2021 artificial

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發(fā)表于 2025-3-21 18:30:01 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Big Data
期刊簡稱8th CCF Conference,
影響因子2023Hong Mei,Weiguo Zhang,Li Wang
視頻videohttp://file.papertrans.cn/186/185569/185569.mp4
學(xué)科分類Communications in Computer and Information Science
圖書封面Titlebook: Big Data; 8th CCF Conference,  Hong Mei,Weiguo Zhang,Li Wang Conference proceedings 2021 Springer Nature Singapore Pte Ltd. 2021 artificial
影響因子This book constitutes the proceedings of the 8th CCF Conference on Big Data, BigData 2020, held in Chongqing, China, in October 2020..The 16 full papers presented in this volume were carefully reviewed and selected from 65 submissions. They present recent research on?theoretical and technical aspects on big data, as well as on digital economy demands in big data applications.?.
Pindex Conference proceedings 2021
The information of publication is updating

書目名稱Big Data影響因子(影響力)




書目名稱Big Data影響因子(影響力)學(xué)科排名




書目名稱Big Data網(wǎng)絡(luò)公開度




書目名稱Big Data網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Big Data被引頻次




書目名稱Big Data被引頻次學(xué)科排名




書目名稱Big Data年度引用




書目名稱Big Data年度引用學(xué)科排名




書目名稱Big Data讀者反饋




書目名稱Big Data讀者反饋學(xué)科排名




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Violence as Deviance? The Societal Response,rate that our proposed method achieves the competitive performance compared with the state-of-the-art deep learning methods and numerically promotes the reconstruction accuracy considerably, showing the effectiveness of the proposed NAS-CSNet and the promise to further use of NAS in the CS field.
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Violence as Deviance? The Societal Response,urve; 2) MELP is more excellent in AUC value. MELP algorithm can provide an entirely new solution to the precision delivery of Internet advertisements, the perception of users’ risky behaviors and other applications.
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A. Dexter Samuels,Rahn Kennedy Baileyraining process. As different customers have different food tastes, we have improved our method and invented new model using Conditional GAN (CGAN) to incorporate the personal demands in food pairing. We have conducted extensive experiments on real data sets to evaluate the efficiency of our propose
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https://doi.org/10.1007/978-3-030-44762-5ollaborative filtering), using Embedding technology and graph convolutional neural network to mine the attributes and interactive relationship features in the data, and then through the fusion of feature vector expressions to achieve personalized exercise program recommendations. The design and impl
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