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Titlebook: Data Mining and Big Data; 7th International Co Ying Tan,Yuhui Shi Conference proceedings 2022 The Editor(s) (if applicable) and The Author(

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書目名稱Data Mining and Big Data
副標(biāo)題7th International Co
編輯Ying Tan,Yuhui Shi
視頻videohttp://file.papertrans.cn/263/262916/262916.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Data Mining and Big Data; 7th International Co Ying Tan,Yuhui Shi Conference proceedings 2022 The Editor(s) (if applicable) and The Author(
描述This two-volume set, CCIS 1744 and CCIS 1745 book constitutes the 7th International Conference, on Data Mining and Big Data, DMBD 2022, held in Beijing, China,?in November 21–24, 2022..The 62 full papers presented in this two-volume set included in this book were carefully reviewed and selected from 135 submissions. The papers present the latest research on?advantages in theories, technologies, and applications in data mining and big data. The volume covers many aspects of data mining and big data as well as intelligent computing methods applied to all fields of computer science, machine learning, data mining and knowledge discovery, data science, etc..
出版日期Conference proceedings 2022
關(guān)鍵詞artificial intelligence; computer networks; computer systems; computer vision; data mining; image analysi
版次1
doihttps://doi.org/10.1007/978-981-19-9297-1
isbn_softcover978-981-19-9296-4
isbn_ebook978-981-19-9297-1Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

書目名稱Data Mining and Big Data影響因子(影響力)




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Flow Prediction via?Multi-view Spatial-Temporal Graph Neural Network get the final prediction results. Comprehensive experiments on two datasets showed that the proposed framework has very high prediction performance, and outperforms the baseline model by more than 6%.
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Research and Analysis of Video-Based Human Pose Estimationally constructed features of pose angles, relative displacements, moving pattern sequences and etc. are calculated. These informative features enlighten people of latent motion rules. Finally, we report how our framework is applied to realistic classification datasets. Through our work, an overall s
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