Data Science: 11th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2025, Hiroshima, Japan, September 1921, Proceedings: 2673

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Bol This book constitutes the refereed proceedings of the 11th International Conference on Data Science, ICPCSEE 2025, held in Hiroshima, Japan, during September 19–21, 2025. The 41 full papers and 1 short papers included in this book were carefully reviewed and selected from 135 submissions. This book constitutes the refereed proceedings of the 11th International Conference on Data Science, ICPCSEE 2025, held in Hiroshima, Japan, during September 19–21, 2025. The 41 full papers and 1 short papers included in this book were carefully reviewed and selected from 135 submissions. They were organized in topical sections as follows: Education using big data, intelligent computing or data mining, etc.; Education research, methods and materials for data science and engineering; Machine Learning for Data Science; Basic Theory and Techniques for Data Science; Application of Blockchain; Big Data Management and Applications; Industrial Digitization and Applications; Applications of Data Science; Data Security and Privacy; Data-driven Scientific Research; and Novel methods for data analytics.

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This book constitutes the refereed proceedings of the 11th International Conference on Data Science, ICPCSEE 2025, held in Hiroshima, Japan, during September 19–21, 2025. The 41 full papers and 1 short papers included in this book were carefully reviewed and selected from 135 submissions. This book constitutes the refereed proceedings of the 11th International Conference on Data Science, ICPCSEE 2025, held in Hiroshima, Japan, during September 19–21, 2025. The 41 full papers and 1 short papers included in this book were carefully reviewed and selected from 135 submissions. They were organized in topical sections as follows: Education using big data, intelligent computing or data mining, etc.; Education research, methods and materials for data science and engineering; Machine Learning for Data Science; Basic Theory and Techniques for Data Science; Application of Blockchain; Big Data Management and Applications; Industrial Digitization and Applications; Applications of Data Science; Data Security and Privacy; Data-driven Scientific Research; and Novel methods for data analytics.


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