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 book presents a range of new developments in the theory and practice of multivariate statistical data analysis. Several contributions illustrate the use of multivariate methods in application fields such as economics, medicine, environment, and biology.

This book deals with recent developments in classification and data analysis and presents new topics which are of central interest to modern statistics. In particular, these include: classification models and clustering methods, multivariate data analysis, symbolic data, neural networks and learning devices, phylogeny and bioinformatics, new software systems for classification and data analysis, as well as applications in social, economic, biological, medical and other sciences. The book presents a long list of useful methods for classification, clustering and data analysis. By combining theoretical aspects with practical problems it is designed for researchers as well as for applied statisticians and will support the fast transfer of new methodological advances to a wide range of applications.

This first systematic and self-contained monograph on "Symbolic Data Analysis" presents the most recent methods for analyzing and visualizing symbolic data. It generalizes classical methods of exploratory, statistical and graphical data analysis to the case of complex data where the entries of a data table are, e. g., sets of categories or of numbers, intervals or probability distributions. Typical methods include: graphical displays using Zoom Stars, visualization and feature extraction by symbolic factor analysis, decision trees, discrimination, classification and clustering methods. Several benchmark examples from National Statistical Offices illustrate the usefulness of the methods. The book contains an extensive bibliography and a subject index.

International Federation of Classification Societies The International Federation of Classification Societies (lFCS) is an agency for the dissemination of technical and scientific information concerning classification and multivariate data analysis in the broad sense and in as wide a range of applications as possible; founded in 1985 in Cambridge (UK) by the following Scientific Societies and Groups: - British Classification Society - BCS - Classification Society of North America - CSNA - Gesellschaft fUr Klassification - GfKI - Japanese Classification Society - JCS - Classification Group ofItalian Statistical Society - CGSIS - Societe Francophone de Classification - SFC Now the IFCS includes also the following Societies: - Dutch-Belgian Classification Society - VOC - Polish Classification Section - SKAD - Portuguese Classification Association - CLAD - Group at Large - Korean Classification Society - KCS IFCS-98, the Sixth Conference of the International Federation of Classification Societies, was held in Rome, from July 21 to 24, 1998. Five preceding conferences were held in Aachen (Germany), Charlottesville (USA), Edinburgh (UK), Paris (France), Kobe (Japan).

This volume presents 45 articles dealing with theoretical aspects, methodo logical advances and practical applications in domains relating to classifica tion and clustering, statistical and computational data analysis, conceptual or terminological approaches for information systems, and knowledge struc tures for databases. These articles were selected from about 140 papers presented at the 19th Annual Conference of the Gesellschaft fur Klassifika tion, the German Classification Society. The conference was hosted by W. Polasek at the Institute of Statistics and Econometry of the University of 1 Basel (Switzerland) March 8-10, 1995 . The papers are grouped as follows, where the number in parentheses is the number of papers in the chapter. 1. Classification and clustering (8) 2. Uncertainty and fuzziness (5) 3. Methods of data analysis and applications (7) 4. Statistical models and methods (4) 5. Bayesian learning (5) 6. Conceptual classification, knowledge ordering and information systems (12) 7. Linguistics and dialectometry (4). These chapters are interrelated in many respects. The reader may recogni ze, for example, the analogies and distinctions existing among classification principles developed in such different domains as statistics and information sciences, the benefit to be gained by the comparison of conceptual and ma thematical approaches for structuring data and knowledge, and, finally, the wealth of practical applications described in many of the papers. For convenience of the reader, the content of this volume is briefly reviewed.

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.

In science, industry, public administration and documentation centers 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 a wealth of new and innovative ideas, methods, models and systems which can be used for this purpose. It combines papers and strategies from two main streams of research in an interdisciplinary, dynamic and exciting way: On the one hand, mathematical and statistical methods are described which allow a quantitative analysis of data, provide strategies for classifying objects or making exploratory searches for interesting structures, and give ways to make comprehensive graphical displays of large arrays of data. On the other hand, papers related to information sciences, informatics and data bank systems provide powerful tools for representing, modelling, storing and retrieving facts, data and knowledge characterized by qualitative descriptors, semantic relations, or linguistic concepts. The integration of both fields and a special part on applied problems from biology, medicine, archeology, industry and administration assure that this volume will be informative and useful for theory and practice.

This volume contains selected papers presented at two joint German-Japanese symposia on data analysis and related elds. The articles substantially extend and further develop material presented at the two symposia organized on the basis of longstanding and close relationships which have been cultivated in the last couple of decades between the two classi cation societies: the German Class- cation Society (Gesellschaft fu ]r Klassi kation e. V.) and the Japanese Classi cation Society. These symposia have been very helpful in exchanging ideas, views, and knowledge between the two societies and have served as a spring board for more extensive and closer co-operation between the societies as well as among their individual members. The scienti c program of the rst Joint Japanese-German Symposium (Tokyo 2005)included23presentations;forthesecondJointGerman-JapaneseSymposium (Berlin 2006) 27 presentations were scheduled. This volume presents 21 peer refereed papers, which are grouped into three parts: 1. Part 1 Clustering and Visualization (eight papers) 2. Part 2 Methods in Fields (nine papers) 3. Part 3 Applications in Clustering and Visualization (four papers) The concept of having a joint symposium of the two classi cation societies came from the talks with Hans-Hermann and Wolfgang when Akinori attended the 28th Annual Conference of the German Classi cation Society held in Dortmund in March 2004."