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Titlebook: Knowledge Science, Engineering and Management; 16th International C Zhi Jin,Yuncheng Jiang,Wenjun Ma Conference proceedings 2023 The Editor

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發(fā)表于 2025-3-21 17:50:20 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Knowledge Science, Engineering and Management
副標(biāo)題16th International C
編輯Zhi Jin,Yuncheng Jiang,Wenjun Ma
視頻videohttp://file.papertrans.cn/545/544049/544049.mp4
叢書(shū)名稱Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Knowledge Science, Engineering and Management; 16th International C Zhi Jin,Yuncheng Jiang,Wenjun Ma Conference proceedings 2023 The Editor
描述This volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16–18, 2023.?.The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management systems; and emerging technologies for knowledge science, engineering and management.?
出版日期Conference proceedings 2023
關(guān)鍵詞artificial intelligence; computational linguistics; computer networks; data mining; databases; directed g
版次1
doihttps://doi.org/10.1007/978-3-031-40292-0
isbn_softcover978-3-031-40291-3
isbn_ebook978-3-031-40292-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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0302-9743 KSEM 2023, which was held in Guangzhou, China, during August 16–18, 2023.?.The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge en
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Federated Prompting and?Chain-of-Thought Reasoning for?Improving LLMs Answeringificantly more accurate answers for all user queries without requiring sophisticated model-tuning. Through extensive experiments, we demonstrate that our proposed methods can significantly enhance question accuracy by fully exploring the synonymous nature of the questions and the consistency of the answers.
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Jian Yang,Xinyu Hu,Weichun Huang,Hao Yuan,Yulong Shen,Gang Xiaochaden durch ungeprüftes Umsetzen von Forschungsergebnissen in Technologien angerichtet, da? es ernsthafter und umfangreicher Forschungsarbeiten bedarf, die Sch?den zu erkennen, zu beseitigen und durch verbesserte Technologien dauerhaft zu vermeiden.
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Xianwei Zhou,Xin Ye,Kun Zhang,Songsen Yuchaden durch ungeprüftes Umsetzen von Forschungsergebnissen in Technologien angerichtet, da? es ernsthafter und umfangreicher Forschungsarbeiten bedarf, die Sch?den zu erkennen, zu beseitigen und durch verbesserte Technologien dauerhaft zu vermeiden.
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