Data Analysis de Wolfgang A. Gaul

Data Analysis

Wolfgang A. Gaul

Otto Opitz

Martin Schader

"Data Analysis" in the broadest sense is the general term for a field of activities of ever-increasing importance in a time called the information age. It covers new areas with such trendy labels as, e.g., data mining or web mining as well as traditional directions emphazising, e.g., classification or knowledge organization. Leading researchers in data analysis have contributed to this volume and delivered papers on aspects ranging from scientific modeling to practical application. They have devoted their latest contributions to a book edited to honor a colleague and friend, Hans-Hermann Bock, who has been active in this field for nearly thirty years.

Citește tot Restrânge

Cuprins

I. Classification.- Clustering Relational Data.- An Iterative Relocation Algorithm for Classifying Symbolic Data.- Automatic Classification with Classifying Automata.- Classification and Clustering of Objects With Variants.- Non-Hierarchical Classification Structures.- Clustering and Classification Based on Expert Knowledge Propagation Using a Probabilistic Self-Organizing Map.- II. Data Analysis.- Unobserved Heterogeneity in Mean- and Covariance Structure Models.- Average Consensus in Numerical Taxonomy and Some Generalizations.- Exploring Multivariate Modality by Unsupervised Mixture of Cubic B-Splines in 1-D Using Model Selection Criteria.- On a Framework for Dissimilarity Analysis.- Least-Squares Ultrametric Tree Representations of Three-Way One-Mode Proximity Data.- From Data Mining to Knowledge Mining: An Introduction to Symbolic Data Analysis.- Evidence for a Relationship Between Algorithmic Scheme and Shape of Inferred Trees.- Testing for Antimodes.- A Classification of Bivariate Negative Binomial Distributions.- Robust Forecasting of Parametric Trend of Time Series under “Outliers”.- Projections Distinguishing Isolated Groups in Multivariate Data Spaces.- Non-Symmetrical Data Analysis Approaches: Recent Developments and Perspectives.- Contiguity Analysis and Classification.- New Results in Cutting Seriation for Approximate #SAT.- Applied Bayesian Data Analysis Using State-Space Models.- Intelligent Data Modeling Based on the Wavelet Transform and Data Entropy.- A Characterization of Ordinal Data.- Generalized Impulse Response Functions for VAR-GARCH-M Models.- A New Geometrical Hypothesis for Partitioning and Discriminant Analysis.- Ultrametrics and p-adic Numbers.- An Algorithm for Positive-Breakdown Regression Based on Concentration Steps.- UnidimensionalStructure Detected by Analysis of an Asymmetric Data Matrix.- A Geometrical Relational Model for Data Analysis.- Towards a Statistical Theory of Optimal Quantization.- Robust Clustering.- III. Applications.- Bump Hunting for Risk: A New Data Mining Tool.- Clusters of Bibliographic References: A Brief Case Study.- Online Classification of States in Intensive Care.- Frequent Generalized Subsequences — A Problem From Web Mining.- myVU: A Next Generation Recommender System Based on Observed Consumer Behavior and Interactive Evolutionary Algorithms.- Global Optimization Methods for Multidimensional Scaling Applied to Mobile Communication.- Synergy in Drug Combinations.- Maximum Likelihood Clustering for Elasticity-Based Market Segmentation.- Statistics and Data Analysis in Market Risk Measurement.- An Asymmetric Cluster Analysis Study of Car Switching Data.- Visualization of Multivariate Data by Scaling and Property Fitting.- Facts and Problems in the Lung Cancer Medical Cost Analysis Through Claims Data.- Selected Publications of Hans-Hermann Bock.