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Titlebook: Computer Science and Education; 17th International C Wenxing Hong,Yang Weng Conference proceedings 2023 The Editor(s) (if applicable) and T

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樓主
發(fā)表于 2025-3-21 18:11:13 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computer Science and Education
副標(biāo)題17th International C
編輯Wenxing Hong,Yang Weng
視頻videohttp://file.papertrans.cn/234/233785/233785.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Computer Science and Education; 17th International C Wenxing Hong,Yang Weng Conference proceedings 2023 The Editor(s) (if applicable) and T
描述This three-volume set constitues selected papers presented during the?17th International Conference on Computer Science and Education, ICCSE 2022, held in Ningbo, China, in August 2022..The 168 full papers and 43 short papers presented were thoroughly reviewed and selected from the 510 submissions. They focus on?a wide range of computer science topics, especially AI, data science, and engineering, and technology-based education, by addressing frontier technical and business issues essential to the applications of data science in both higher education and advancing e-Society..
出版日期Conference proceedings 2023
關(guān)鍵詞education technology; applied computing; systems security; artificial intelligence; data management syst
版次1
doihttps://doi.org/10.1007/978-981-99-2443-1
isbn_softcover978-981-99-2442-4
isbn_ebook978-981-99-2443-1Series 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Computer Science and Education影響因子(影響力)




書目名稱Computer Science and Education影響因子(影響力)學(xué)科排名




書目名稱Computer Science and Education網(wǎng)絡(luò)公開度




書目名稱Computer Science and Education網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computer Science and Education被引頻次




書目名稱Computer Science and Education被引頻次學(xué)科排名




書目名稱Computer Science and Education年度引用




書目名稱Computer Science and Education年度引用學(xué)科排名




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Topic Term Clustering Based on?Semi-supervised Co-occurrence Graph and?Its Application in?Chinese Jued by the uncertainty of law and facts, but also affected by the judge’s discretion and factors outside the case. So it is difficult to format controversial issues and inappropriate to judge the similarity by the consistency of controversial issues. Meanwhile, controversial issues data is subject to
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A Method of Students’ Online Learning Status Analysis Based on Facial Expressionreached 82.5%. Three types of visualizations presented in this paper (individual real-time feedback, feedback on the learning status of the class, and analysis feedback charts) provide students and instructors with privacy-preserving feedback on learning status.
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Short Text Dynamic Clustering Approach for Semantic-Enhanced Knowledge of semantic knowledge can automatically adjust the strength of topic inheritance, making the dynamic evolution of the number of clusters more in line with the actual data. Experiments on synthetic data and real data show that the SDDMM model effectively improves the short texts’ dynamic clustering
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Comparison Between Methods Based on LSTM and BLS for Stock Analysis and Prediction the weight of each layer of LSTM is updated by gradient layer by layer, while the weight from hidden layer to output layer in BLS model is solved by pseudo-inverse calculation, which avoids the gradient update method and ensures the efficiency of network training. In addition, the BLS-based loop st
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The Uncemented Thrust-Plate Hip Prosthesis,e Tracing (SATCN). It can take the historical exercises of each learner as input and model the individual learning in a consistent manner that means it can realize personalized knowledge tracking prediction without extra manipulations. Moreover, with the self attention mechanism our model can adjust
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International Astronomical Union Symposiareached 82.5%. Three types of visualizations presented in this paper (individual real-time feedback, feedback on the learning status of the class, and analysis feedback charts) provide students and instructors with privacy-preserving feedback on learning status.
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