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Titlebook: Recent Challenges in Intelligent Information and Database Systems; 14th Asian Conferenc Edward Szczerbicki,Krystian Wojtkiewicz,Marek Krót

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發(fā)表于 2025-3-21 20:08:53 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Recent Challenges in Intelligent Information and Database Systems
副標(biāo)題14th Asian Conferenc
編輯Edward Szczerbicki,Krystian Wojtkiewicz,Marek Krót
視頻videohttp://file.papertrans.cn/824/823091/823091.mp4
叢書(shū)名稱(chēng)Communications in Computer and Information Science
圖書(shū)封面Titlebook: Recent Challenges in Intelligent Information and Database Systems; 14th Asian Conferenc Edward Szczerbicki,Krystian Wojtkiewicz,Marek Krót
描述This book constitutes the refereed proceedings of the?14th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2022, held in Ho Chi Minh City, Vietnam, in November 2022.??.?This volume contains 60 peer-reviewed papers selected for poster presentation from 406 submissions. Papers included in this volume cover the following topics: data mining and machine learning methods, advanced data mining techniques and applications, intelligent and contextual systems, natural language processing, network systems and applications, computational imaging and vision, decision support and control systems, and data modeling and processing for industry 4.0.
出版日期Conference proceedings 2022
關(guān)鍵詞artificial intelligence; computational linguistics; computer vision; correlation analysis; data mining; d
版次1
doihttps://doi.org/10.1007/978-981-19-8234-7
isbn_softcover978-981-19-8233-0
isbn_ebook978-981-19-8234-7Series 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
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978-981-19-8233-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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,Machine Learning-Based Recommender System for?Tweeting Factory in?Industry 5.0 Paradigm,asic concepts are discussed. It is indicated how the proposed solution fulfills the requirements concerning Industry 5.0 paradigm. The system also utilizes the idea of the Tweeting Factory [.] paradigm, making it easy to apply in various industry branches.
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,Exploring the?Effect of?Vehicle Appearance and?Motion for?Natural Language-Based Vehicle Retrieval,iency of each contribution in the overall framework. It confirms that not only appearance but additional motion cues are promising for vehicle retrieval, which provides the results of MRR, Rank@5 and Rank@10 are 0.2333, 0.3587 and 0.4837, respectively.
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,Explaining Predictive Scheduling in?Cloud,n terms of computation. This paper first predicts resource usage in terms of CPU by applying the lightGBM model to a real dataset. Furthermore, using the explanations of SHapley Additive exPlanations (SHAP) in combination with the K-Nearest Neighbor (KNN) to interpolate missing values in the dataset
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