Hans-Hermann Bock – författare

The book presents a range of new developments in the theory and practice of multivariate statistical data analysis. Among the topics are the construction and comparison of classification trees, clustering methods, generalized multivariate distributions, the analysis of symbolic data, explorative time series analysis, smoothing and dynamic regression models, generalized linear models, and neural networks. Several contributions illustrate the use of multivariate methods in application fields such as economics, medicine, environment, and biology.

Data Science and Classification provides new methodological developments in data analysis and classification. The broad and comprehensive coverage includes the measurement of similarity and dissimilarity, methods for classification and clustering, network and graph analyses, analysis of symbolic data, and web mining. Beyond structural and theoretical results, the book offers application advice for a variety of problems, in medicine, microarray analysis, social network structures, and music.

The present volume contains a selection of papers presented at the Eighth Conference of the International Federation of Classification Societies (IFCS) which was held in Cracow, Poland, July 16-19, 2002. All originally submitted papers were subject to a reviewing process by two independent referees, a procedure which resulted in the selection of the 53 articles presented in this volume. These articles relate to theoretical investigations as well as to practical applications and cover a wide range of topics in the broad domain of classifi­ cation, data analysis and related methods. If we try to classify the wealth of problems, methods and approaches into some representative (partially over­ lapping) groups, we find in particular the following areas: • Clustering • Cluster validation • Discrimination • Multivariate data analysis • Statistical methods • Symbolic data analysis • Consensus trees and phylogeny • Regression trees • Neural networks and genetic algorithms • Applications in economics, medicine, biology, and psychology. Given the international orientation of IFCS conferences and the leading role of IFCS in the scientific world of classification, clustering and data anal­ ysis, this volume collects a representative selection of current research and modern applications in this field and serves as an up-to-date information source for statisticians, data analysts, data mining specialists and computer scientists.

In science, industry, public administration and documentation centres, large amounts of data and information are collected which must be analyzed, ordered, visualized, classified and stored efficiently in order to be useful for practical applications. This volume contains 50 selected theoretical and applied papers presenting ideas, methods, models and systems which can be used for this purpose. It combines papers and strategies from two main areas of research - theoretical and applied. Mathematical and statistical methods, which allow quantitative analysis of data are detailed, suggestions are made as to how to provide strategies for classifying objects or to make exploratory searches for interesting structures and means are suggested by which to construct finely detailed graphical displays of large arrays of data. Papers related to information sciences, informatics and data bank systems provide descriptions of powerful tools for representing, modelling, storing and retrieving facts, data and knowledge characterized by qualitative descriptors, semantic relations, or linguistic concepts.A section relevant to applied problems from biology, medicine, archaeology, industry and administration is included.

This volume presents a selection of 42 refereed and revised contributions (includ- ing some invited lectures) which were presented at the 17th Annual Conference of the "Gesellschaft fur Klassifikation e. V." (GfKl), the German Classification Society. This conference was held at the University of Kaiserslautern from March 3 - 5, 1993 and jointly hosted by the Research Center for Mathematical Logic of the Heidelberg Academy for the Humanities and Sciences, the University of Kaiserslautern, and the German Research Center for Artificial Intelligence (DFKI GmbH). The local orga- nization was performed by Michael M. Richter, Wolfgang Lenski, Sabine Friedrich, Annette Klein, and Elisabeth Wette-Roch of the Computer Science Department of the University of Kaiserslautern and the Research Center for Mathematical Logic of the Heidelberg Academy for the Humanities and Sciences, respectively. The mem- bers of the Scientific Program Committee were Hans-Hermann Bock, PaulO. Degens, Matthias Herfurth, Hans-Joachim Hermes, Rudiger Klar, Rudolf Mathar, Michael M. Richter, and Rudolf Wille.

This volume presents methods for the analysis of quantitative and qualitative data, and for the processing and ordering of symbolic or linguistic information. The 45 papers combine methods from exploratory and inferential statistics with mathematical and numerical approaches, investigate conceptual classification and ordering structures and describe recent developments for knowledge-based information systems. The contributions are grouped into seven chapters: 1. Classification and Clustering, 2. Uncertainty and Fuzziness, 3. Methods of Data Analysis and Applications, 4. Statistical Models and Methods, 5. Bayesian Learning, 6. Conceptual Classification, Knowledge Ordering and Information Systems, 7. Linguistics and Dialectometry.

The book provides new developments in classification and data analysis, and presents new topics which are of central interest to modern statistics. In particular, these include classification theory, multivariate data analysis, multi-way data, proximity structure analysis, new software for classification and data analysis, and applications in social, economic, medical and other sciences. For many of these topics, this book provides a systematic state of the art written by top researchers in the world. This book will serve as a helpful introduction to the area of classification and data analysis for research workers and support the transfer of new advances in data science and classification to a wide range of applications.

Raymond Bisdorff CRP-GL, Luxembourg The development of the SODAS software based on symbolic data analysis was extensively described in the previous chapters of this book. It was accompanied by a series of benchmark activities involving some official statistical institutes throughout Europe. Partners in these benchmark activities were the National Statistical Institute (INE) of Portugal, the Instituto Vasco de Estadistica Euskal (EUSTAT) from Spain, the Office For National Statistics (ONS) from the United Kingdom, the Inspection Generale de la Securite Sociale (IGSS) from Luxembourg 1 and marginally the University of Athens . The principal goal of these benchmark activities was to demonstrate the usefulness of symbolic data analysis for practical statistical exploitation and analysis of official statistical data. This chapter aims to report briefly on these activities by presenting some signifi­ cant insights into practical results obtained by the benchmark partners in using the SODAS software package as described in chapter 14 below.