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Titlebook: Data Science and Algorithms in Systems; Proceedings of 6th C Radek Silhavy,Petr Silhavy,Zdenka Prokopova Conference proceedings 2023 The Ed

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書目名稱Data Science and Algorithms in Systems
副標(biāo)題Proceedings of 6th C
編輯Radek Silhavy,Petr Silhavy,Zdenka Prokopova
視頻videohttp://file.papertrans.cn/264/263073/263073.mp4
概述Presents the latest research on Software Engineering Application in Informatics.Gathers the Proceedings of the 6th Computational Methods in Systems and Software 2022 (CoMeSySo2022) conference.Written
叢書名稱Lecture Notes in Networks and Systems
圖書封面Titlebook: Data Science and Algorithms in Systems; Proceedings of 6th C Radek Silhavy,Petr Silhavy,Zdenka Prokopova Conference proceedings 2023 The Ed
描述.This book offers real-world data science and algorithm design topics linked to systems and software engineering. Furthermore, articles describing unique techniques in data science, algorithm design, and systems and software engineering are featured...This book is the second part of the refereed proceedings of the 6th Computational Methods in Systems and Software 2022 (CoMeSySo 2022). The CoMeSySo 2022 conference, which is being hosted online, is breaking down barriers. CoMeSySo 2022 aims to provide a worldwide venue for debate of the most recent high-quality research findings..
出版日期Conference proceedings 2023
關(guān)鍵詞Software Engineering; Software Engineeering Applications; CoMeSySo; Computational Methods in Systems an
版次1
doihttps://doi.org/10.1007/978-3-031-21438-7
isbn_softcover978-3-031-21437-0
isbn_ebook978-3-031-21438-7Series ISSN 2367-3370 Series E-ISSN 2367-3389
issn_series 2367-3370
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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Conceptual Linked Data Model for South African Municipalities Public Services Domain, during the modeling phase. Finally, we present a conceptually linked municipality data ontology in Web Ontology Language (OWL), supported by the y Protégé ontology management tool, that models the public services domain, thus allowing the standardization and interoperability of respective municipalities’ departments.
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Daniel Kossmann,Donald Kossmannis proving difficult. The purpose of this article is to conduct a literature study of classification algorithms to predict, prevent, and detect mental health disorders. Some of the algorithms studied include Random Forest, SVM, and Deep Learning.
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