German-Japanese Interchange of Data Analysis Results

1. Front Matter

   Pages i-xiii

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2. Clustering

   1. Front Matter

      Pages 1-1

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   2. Model-Based Clustering Methods for Time Series

      • Hans-Hermann Bock

      Pages 3-15

   3. The Randomized Greedy Modularity Clustering Algorithm and the Core Groups Graph Clustering Scheme

      • Andreas Geyer-Schulz, Michael Ovelgönne

      Pages 17-36

   4. Comparison of Two Distribution Valued Dissimilarities and Its Application for Symbolic Clustering

      • Yusuke Matsui, Yuriko Komiya, Hiroyuki Minami, Masahiro Mizuta

      Pages 37-46

   5. Pairwise Data Clustering Accompanied by Validation and Visualisation

      • Hans-Joachim Mucha

      Pages 47-57

   6. Classification, Clustering, and Visualisation Based on Dual Scaling

      • Hans-Joachim Mucha

      Pages 59-69

   7. Variable Selection in K-Means Clustering via Regularization

      • Yutaka Nishida

      Pages 71-79

   8. Structural Representation of Categorical Data and Cluster Analysis Through Filters

      • Shizuhiko Nishisato

      Pages 81-90

   9. Three-Mode Hierarchical Subspace Clustering with Noise Variables and Occasions

      • Kensuke Tanioka, Hiroshi Yadohisa

      Pages 91-99

3. Analysis of Data and Models

   1. Front Matter

      Pages 101-101

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   2. Bayesian Methods for Conjoint Analysis-Based Predictions: Do We Still Need Latent Classes?

      • Daniel Baier

      Pages 103-113

   3. Non-additive Utility Functions: Choquet Integral Versus Weighted DNF Formulas

      • Eyke Hüllermeier, Ingo Schmitt

      Pages 115-123

   4. A Symmetry Test for One-Mode Three-Way Proximity Data

      • Atsuho Nakayama, Hiroyuki Tsurumi, Akinori Okada

      Pages 125-134

   5. Analysis of Conditional and Marginal Association in One-Mode Three-Way Proximity Data

      • Atsuho Nakayama

      Pages 135-146

   6. Analysis of Asymmetric Relationships Among Soft Drink Brands

      • Akinori Okada

      Pages 147-156

   7. Automatic Regularization of Factorization Models

      • Steffen Rendle

      Pages 157-166

   8. Three-Way Data Analysis for Multivariate Spatial Time Series

      • Mitsuhiro Tsuji, Hiroshi Kageyama, Toshio Shimokawa

      Pages 167-175

4. Applications

   1. Front Matter

      Pages 177-177

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   2. Assessment of the Relationship Between Native Thoracic Aortic Curvature and Endoleak Formation After TEVAR Based on Linear Discriminant Analysis

      • Kuniyoshi Hayashi, Fumio Ishioka, Bhargav Raman, Daniel Y. Sze, Hiroshi Suito, Takuya Ueda et al.

      Pages 179-192

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). 

• Applied Statistics
• Clustering
• Computing Methodologies
• Data Analysis

• Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

  Wolfgang Gaul, Andreas Geyer-Schulz

• The Institute of Statistical Mathematics, Tokyo, Japan

  Yasumasa Baba

• Graduate School of Management and Information Systems, Tama University, Tokyo, Japan

  Akinori Okada

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