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This book constitutes the refereed proceedings of the 98th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2021, held in Ishikawa, Japan, in March 2022.

The 30 full papers presented were carefully reviewed and selected from 46 submissions. The papers deal with all aspects of uncertainty modelling and management and are organized in topical sections on uncertainty management and decision making, optimization and statistical methods, pattern classification and data analysis, machine learning, and economic applications.

This two-volume set constitutes the proceedings of the 11th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2025, held in Ho Chi Minh City, Vietnam, during March 17-19, 2025.  The 55 full papers in this book were carefully reviewed and selected from 116 submissions. They were organized in topical sections as follows:  Part I: Invited Talks; Machine Learning; Pattern Recognition and Data Analysis; Applications. Part II: Uncertainty Management and Decision Making; Optimization and Statistical Methods; Applications.

This two-volume set constitutes the proceedings of the 11th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2025, held in Ho Chi Minh City, Vietnam, during March 17-19, 2025.  The 55 full papers in this book were carefully reviewed and selected from 116 submissions. They were organized in topical sections as follows:  Part I: Invited Talks; Machine Learning; Pattern Recognition and Data Analysis; Applications. Part II: Uncertainty Management and Decision Making; Optimization and Statistical Methods; Applications.

Recently many researchers are working on cluster analysis as a main tool for exploratory data analysis and data mining. A notable feature is that specialists in di?erent ?elds of sciences are considering the tool of data clustering to be useful. A major reason is that clustering algorithms and software are ?exible in thesensethatdi?erentmathematicalframeworksareemployedinthealgorithms and a user can select a suitable method according to his application. Moreover clusteringalgorithmshavedi?erentoutputsrangingfromtheolddendrogramsof agglomerativeclustering to more recent self-organizingmaps....