Topics
The conference addresses current research
on Data Analysis, Machine Learning, Data Mining,
Pattern Recognition, and Applied Statistics
as well as applications to a broad range of areas
with special emphasis on
interdisciplinarity and
the interaction between theory and practice.
Topics include but are not limited to:
Theory and Methods
- Supervised Classification, Discrimination, and
Pattern Recognition
(G. Ritter)
- Cluster Analysis and Similarity Structures
(H.-H. Bock and J. Buhmann)
- Classification and Regression
(C. Hennig)
- Frequent Pattern Mining
(C. Borgelt)
- Data Visualization and Scaling Methods
(P. Groenen, T. Imaizumi, and A. Okada)
- Exploratory Data Analysis and Data Mining
(M. Meyer and M. Schwaiger)
- Mixture Analysis in Clustering
(W. Seidel)
- Computational Intelligence
(R. Kruse)
- Knowledge Representation and Knowledge
Discovery
(A. Ultsch)
- Statistical Relational Learning
(H. Blockeel and K. Kersting)
- Online Algorithms and Data Streams
(C. Sohler)
- Analysis of Time Series, Longitudinal and Panel Data
(S. Lang)
- Tools for Intelligent Data Analysis
(M. Hahsler and K. Hornik)
- Data Preprocessing and Information Extraction
(H.-J. Lenz)
- Typing for Modeling
(W. Esswein)
Applications
- Marketing and Management Science
(D. Baier, Y. Boztug, and W. Steiner)
- Banking and Finance
(K. Jajuga and H. Locarek-Junge)
- Business Intelligence and Personalization
(A. Geyer-Schulz and L. Schmidt-Thieme)
- Data Analysis in Retailing
(T. Reutterer)
- Econometrics and Operations Research
(W. Polasek)
- Image and Signal Analysis
(H. Burkhardt)
- Biostatistics and Bioinformatics
(R. Backofen and B. Lausen)
- Medical and Health Sciences
(K.-D. Wernecke)
- Text Mining, Web Mining, and the Semantic Web
(A. Nürnberger and M. Spiliopoulou)
- Statistical Natural Language Processing
(P. Cimiano)
- Linguistics
(H. Goebl and P. Grzybek)
- Subject Indexing and Library Science
(H.-J. Hermes and B. Lorenz)
- Statistical Musicology
(C. Weihs)
- Archaeology and Archaeometry
(M. Helfert and I. Herzog)
- Psychology
(S. Krolak-Schwerdt)
- Data Analysis in Higher Education
(A. Hilbert)
Contributed Sessions
- Session 1: Latent class models for classification (A. Montanari and A. Cerioli)
- Session 2: Classification and models for interval-valued data (F. Palumbo)
- Session 3: Selected Problems in Classification (Eugeniusz Gatnar)
- Session 4: Recent Developments in Multidimensional Data Analysis between research and practice I (Luigi D'Ambra)
- Session 5: Recent Developments in Multidimensional Data Analysis between research and practice II (Biagio Simonetti)
