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Titlebook: Recent Advances on Soft Computing and Data Mining; Proceedings of the S Rozaida Ghazali,Nazri Mohd Nawi,Nureize Arbaiy Conference proceedin

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书目名称Recent Advances on Soft Computing and Data Mining
副标题Proceedings of the S
编辑Rozaida Ghazali,Nazri Mohd Nawi,Nureize Arbaiy
视频video
概述Includes recent research on soft computing and data mining.Presents the outcomes of the Sixth International Conference on Soft Computing and Data Mining SCDM-2024.Written by experts in the field
丛书名称Lecture Notes in Networks and Systems
图书封面Titlebook: Recent Advances on Soft Computing and Data Mining; Proceedings of the S Rozaida Ghazali,Nazri Mohd Nawi,Nureize Arbaiy Conference proceedin
描述.This book explores methods for leveraging data to create innovative solutions that offer significant and meaningful value. It provides practical insights into the concepts and techniques essential for maximizing the outcomes of large-scale research and data mining projects. Readers are guided through analytical thinking processes, addressing challenges in deciphering complex data systems and deriving commercial value from the data. Soft computing and data mining, also known as data-driven science, encompass a diverse range of interdisciplinary scientific methods and processes. The proceedings of "Recent Advances on Soft Computing and Data Mining" provide comprehensive knowledge to address various challenges encountered in complex systems. By integrating practices and applications from both domains, it offers a robust framework for tackling these issues. To excel in data-driven ecosystems, researchers, data analysts, and practitioners must carefully select the most suitable approaches and tools. Understanding the design choices and options available is essential for appreciating the underlying concepts, tools, and techniques utilized in these endeavors..
出版日期Conference proceedings 2024
关键词Soft Computing and its Applications; Data Mining and its Applications; Intelligent Computing; SCDM; SCDM
版次1
doihttps://doi.org/10.1007/978-3-031-66965-1
isbn_softcover978-3-031-66964-4
isbn_ebook978-3-031-66965-1Series 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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Alleviating Sparsity to Enhance Group Recommendation with Cross-Linked Domain Model,is study concentrated on data sparsity before the group formation process. The primary goal is to create a cross-domain technique with Linked Open Data (LOD) technology to ensure that problems with data sparsity can be addressed before the group formation process. The experiment of the proposed meth
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Conference proceedings 2024s, researchers, data analysts, and practitioners must carefully select the most suitable approaches and tools. Understanding the design choices and options available is essential for appreciating the underlying concepts, tools, and techniques utilized in these endeavors..
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Rozaida Ghazali,Nazri Mohd Nawi,Nureize ArbaiyIncludes recent research on soft computing and data mining.Presents the outcomes of the Sixth International Conference on Soft Computing and Data Mining SCDM-2024.Written by experts in the field
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Recent Advances on Soft Computing and Data Mining978-3-031-66965-1Series ISSN 2367-3370 Series E-ISSN 2367-3389
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