Yasumasa Baba – författare

This volume focuses on innovative approaches and recent developments in clustering, analysis of data and models, and applications: The first part of the book covers a broad range of innovations in the area of clustering, from algorithmic innovations for graph clustering to new visualization and evaluation techniques. The second part addresses new developments in data and decision analysis (conjoint analysis, non-additive utility functions, analysis of asymmetric relationships, and regularization techniques). The third part is devoted to the application of innovative data analysis methods in the life-sciences, the social sciences and in engineering. All contributions in this volume are revised and extended versions of selected papers presented in the German/Japanese Workshops at Karlsruhe (2010) and Kyoto (2012).

This volume focuses on innovative approaches and recent developments in clustering, analysis of data and models, and applications: The first part of the book covers a broad range of innovations in the area of clustering, from algorithmic innovations for graph clustering to new visualization and evaluation techniques. The second part addresses new developments in data and decision analysis (conjoint analysis, non-additive utility functions, analysis of asymmetric relationships, and regularization techniques). The third part is devoted to the application of innovative data analysis methods in the life-sciences, the social sciences and in engineering. All contributions in this volume are revised and extended versions of selected papers presented in the German/Japanese Workshops at Karlsruhe (2010) and Kyoto (2012).

This volume, Data Science, Classification, and Related Methods, contains a selection of papers presented at the Fifth Conference of the International Federation of Oassification Societies (IFCS-96), which was held in Kobe, Japan, from March 27 to 30,1996. The volume covers a wide range of topics and perspectives in the growing field of data science, including theoretical and methodological advances in domains relating to data gathering, classification and clustering, exploratory and multivariate data analysis, and knowledge discovery and seeking. It gives a broad view of the state of the art and is intended for those in the scientific community who either develop new data analysis methods or gather data and use search tools for analyzing and interpreting large and complex data sets. Presenting a wide field of applications, this book is of interest not only to data analysts, mathematicians, and statisticians but also to scientists from many areas and disciplines concerned with complex data: medicine, biology, space science, geoscience, environmental science, infonnation science, image and pattern analysis, economics, statistics, social sciences, psychology, cognitive science, behavioral science, marketing and survey research, data mining, and knowledge organization.