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Springer-Verlag Berlin Heidelberg 2007
Studies in Classification, Data Analysis,
and Knowledge Organization
Contents
Part I Clustering
Mixture Models for Classification
Gilles Celeux . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
How to Choose the Number of Clusters: The Cramer
Multiplicity Solution
Adriana Climescu-Haulica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Model Selection Criteria for Model-Based Clustering of
Categorical Time Series Data: A Monte Carlo Study
Jos′e G. Dias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Cluster Quality Indexes for Symbolic Classification – An
Examination
Andrzej Dudek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Semi-Supervised Clustering: Application to Image
Segmentation
M′ario A.T. Figueiredo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
A Method for Analyzing the Asymptotic Behavior of the
Walk Process in Restricted Random Walk Cluster Algorithm
Markus Franke, Andreas Geyer-Schulz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Cluster and Select Approach to Classifier Fusion
Eugeniusz Gatnar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Random Intersection Graphs and Classification
Erhard Godehardt, Jerzy Jaworski, Katarzyna Rybarczyk . . . . . . . . . . . . . . 67
Optimized Alignment and Visualization of Clustering Results
Martin Hoffmann, D¨orte Radke, Ulrich M¨oller . . . . . . . . . . . . . . . . . . . . . . . 75
X Contents
Finding Cliques in Directed Weighted Graphs Using Complex
Hermitian Adjacency Matrices
Bettina Hoser, Thomas Bierhance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Text Clustering with String Kernels in R
Alexandros Karatzoglou, Ingo Feinerer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Automatic Classification of Functional Data with Extremal
Information
Fabrizio Laurini, Andrea Cerioli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Typicality Degrees and Fuzzy Prototypes for Clustering
Marie-Jeanne Lesot, Rudolf Kruse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
On Validation of Hierarchical Clustering
Hans-Joachim Mucha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Part II Classification
Rearranging Classified Items in Hierarchies Using
Categorization Uncertainty
Korinna Bade, Andreas N¨urnberger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
Localized Linear Discriminant Analysis
Irina Czogiel, Karsten Luebke, Marc Zentgraf, Claus Weihs . . . . . . . . . . . 133
Calibrating Classifier Scores into Probabilities
Martin Gebel, Claus Weihs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
Nonlinear Support Vector Machines Through Iterative
Majorization and I-Splines
Patrick J.F. Groenen, Georgi Nalbantov, J. Cor Bioch . . . . . . . . . . . . . . . . 149
Deriving Consensus Rankings from Benchmarking
Experiments
Kurt Hornik, David Meyer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
Classification of Contradiction Patterns
Heiko M¨uller, Ulf Leser, Johann-Christoph Freytag . . . . . . . . . . . . . . . . . . . 171
Selecting SVM Kernels and Input Variable Subsets in Credit
Scoring Models
Klaus B. Schebesch, Ralf Stecking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Contents XI
Part III Data and Time Series Analysis
Simultaneous Selection of Variables and Smoothing
Parameters in Geoadditive Regression Models
Christiane Belitz, Stefan Lang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
Modelling and Analysing Interval Data
Paula Brito . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
Testing for Genuine Multimodality in Finite Mixture Models:
Application to Linear Regression Models
Bettina Gr¨un, Friedrich Leisch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
Happy Birthday to You, Mr. Wilcoxon!
Invariance, Semiparametric Efficiency, and Ranks
Marc Hallin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
Equivalent Number of Degrees of Freedom for Neural
Networks
Salvatore Ingrassia, Isabella Morlini . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229
Model Choice for Panel Spatial Models: Crime Modeling in
Japan
Kazuhiko Kakamu, Wolfgang Polasek, Hajime Wago. . . . . . . . . . . . . . . . . . 237
A Boosting Approach to Generalized Monotonic Regression
Florian Leitenstorfer, Gerhard Tutz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
From Eigenspots to Fisherspots – Latent Spaces in the
Nonlinear Detection of Spot Patterns in a Highly Varying
Background
Bjoern H. Menze, B. Michael Kelm, Fred A. Hamprecht . . . . . . . . . . . . . . 255
Identifying and Exploiting Ultrametricity
Fionn Murtagh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263
Factor Analysis for Extraction of Structural Components and
Prediction in Time Series
Carsten Schneider, Gerhard Arminger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273
Classification of the U.S. Business Cycle by Dynamic Linear
Discriminant Analysis
Roland Schuhr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281
XII Contents
Examination of Several Results of Different Cluster Analyses
with a Separate View to Balancing the Economic and
Ecological Performance Potential of Towns and Cities
Nguyen Xuan Thinh, Martin Behnisch, Alfred Ultsch . . . . . . . . . . . . . . . . . 289
Part IV Visualization and Scaling Methods
VOS: A New Method for Visualizing Similarities Between
Objects
Nees Jan van Eck, Ludo Waltman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299
Multidimensional Scaling of Asymmetric Proximities with a
Dominance Point
Akinori Okada, Tadashi Imaizumi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307
Single Cluster Visualization to Optimize Air Traffic
Management
Frank Rehm, Frank Klawonn, Rudolf Kruse . . . . . . . . . . . . . . . . . . . . . . . . . 319
Rescaling Proximity Matrix Using Entropy Analyzed by
INDSCAL
Satoru Yokoyama, Akinori Okada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327
Part V Information Retrieval, Data and Web Mining
Canonical Forms for Frequent Graph Mining
Christian Borgelt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337
Applying Clickstream Data Mining to Real-Time Web
Crawler Detection and Containment Using ClickTips
Platform
An′alia Louren.co, Orlando Belo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351
Plagiarism Detection Without Reference Collections
Sven Meyer zuEissen, Benno Stein, Marion Kulig . . . . . . . . . . . . . . . . . . . . 359
Putting Successor Variety Stemming to Work
Benno Stein, Martin Potthast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367
Collaborative Filtering Based on User Trends
Panagiotis Symeonidis, Alexandros Nanopoulos, Apostolos
Papadopoulos, Yannis Manolopoulos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375
Investigating Unstructured Texts with Latent Semantic
Analysis
Fridolin Wild, Christina Stahl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383
Contents XIII
Part VI Marketing, Management Science and Economics
Heterogeneity in Preferences for Odd Prices
Bernhard Baumgartner, Winfried J. Steiner . . . . . . . . . . . . . . . . . . . . . . . . 393
Classification of Reference Models
Robert Braun, Werner Esswein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401
Adaptive Conjoint Analysis for Pricing Music Downloads
Christoph Breidert, Michael Hahsler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409
Improving the Probabilistic Modeling of Market Basket Data
Christian Buchta. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417
Classification in Marketing Research by Means of
LEM2-generated Rules
Reinhold Decker, Frank Kroll . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425
Pricing Energy in a Multi-Utility Market
Markus Franke, Andreas Kamper, Anke E.er . . . . . . . . . . . . . . . . . . . . . . . 433
Disproportionate Samples in Hierarchical Bayes CBC
Analysis
Sebastian Fuchs, Manfred Schwaiger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441
Building on the Arules Infrastructure for Analyzing
Transaction Data with R
Michael Hahsler, Kurt Hornik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449
Balanced Scorecard Simulator – A Tool for Stochastic
Business Figures
Veit K¨oppen, Marina Allgeier, Hans-J. Lenz . . . . . . . . . . . . . . . . . . . . . . . . . 457
Integration of Customer Value into Revenue Management
Tobias von Martens, Andreas Hilbert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 465
Women’s Occupational Mobility and Segregation in the
Labour Market: Asymmetric Multidimensional Scaling
Miki Nakai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473
Multilevel Dimensions of Consumer Relationships in the
Healthcare Service Market M-L IRT vs. M-L SEM Approach
Iga Rudawska, Adam Sagan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481
XIV Contents
Data Mining in Higher Education
Karoline Sch¨onbrunn, Andreas Hilbert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 489
Attribute Aware Anonymous Recommender Systems
Manuel Stritt, Karen H.L. Tso, Lars Schmidt-Thieme . . . . . . . . . . . . . . . . 497
Part VII Banking and Finance
On the Notions and Properties of Risk and Risk Aversion in
the Time Optimal Approach to Decision Making
Martin Bouzaima, Thomas Burkhardt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 507
A Model of Rational Choice Among Distributions of Goal
Reaching Times
Thomas Burkhardt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515
On Goal Reaching Time Distributions Estimated from DAX
Stock Index Investments
Thomas Burkhardt, Michael Haasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 523
Credit Risk of Collaterals: Examining the Systematic Linkage
between Insolvencies and Physical Assets in Germany
Marc G¨urtler, Dirk Heithecker, Sven Olboeter . . . . . . . . . . . . . . . . . . . . . . . . 531
Foreign Exchange Trading with Support Vector Machines
Christian Ullrich, Detlef Seese, Stephan Chalup . . . . . . . . . . . . . . . . . . . . . . 539
The Influence of Specific Information on the Credit Risk
Level
Miroslaw W′ojciak, Aleksandra W′ojcicka-Krenz . . . . . . . . . . . . . . . . . . . . . . 547
Part VIII Bio- and Health Sciences
Enhancing Bluejay with Scalability, Genome Comparison and
Microarray Visualization
Anguo Dong, Andrei L. Turinsky, Andrew C. Ah-Seng, Morgan
Taschuk, Paul M.K. Gordon, Katharina Hochauer, Sabrina Fr¨ols, Jung
Soh, Christoph W. Sensen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557
Discovering Biomarkers for Myocardial Infarction from
SELDI-TOF Spectra
Christian H¨oner zu Siederdissen, Susanne Ragg, Sven Rahmann . . . . . . . 569
Joint Analysis of In-situ Hybridization and Gene Expression
Data
Lennart Opitz, Alexander Schliep, Stefan Posch . . . . . . . . . . . . . . . . . . . . . 577
Contents XV
Unsupervised Decision Trees Structured by Gene Ontology
(GO-UDTs) for the Interpretation of Microarray Data
Henning Redestig, Florian Sohler, Ralf Zimmer, Joachim Selbig . . . . . . . 585
Part IX Linguistics and Text Analysis
Clustering of Polysemic Words
Laurent Cicurel, Stephan Bloehdorn, Philipp Cimiano . . . . . . . . . . . . . . . . 595
Classifying German Questions According to Ontology-Based
Answer Types
Adriana Davidescu, Andrea Heyl, Stefan Kazalski, Irene Cramer,
Dietrich Klakow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603
The Relationship of Word Length and Sentence Length: The
Inter-Textual Perspective
Peter Grzybek, Ernst Stadlober, Emmerich Kelih . . . . . . . . . . . . . . . . . . . . 611
Comparing the Stability of Different Clustering Results of
Dialect Data
Edgar Haimerl, Hans-Joachim Mucha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 619
Part-of-Speech Discovery by Clustering Contextual Features
Reinhard Rapp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 627
Part X Statistical Musicology and Sound Classification
A Probabilistic Framework for Audio-Based Tonal Key and
Chord Recognition
Benoit Catteau, Jean-Pierre Martens, Marc Leman . . . . . . . . . . . . . . . . . . . 637
Using MCMC as a Stochastic Optimization Procedure for
Monophonic and Polyphonic Sound
Katrin Sommer, Claus Weihs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 645
Vowel Classification by a Neurophysiologically Parameterized
Auditory Model
Gero Szepannek, Tam′as Harczos, Frank Klefenz, Andr′as Katai, Patrick
Schikowski, Claus Weihs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653
XVI Contents
Part XI Archaeology
Uncovering the Internal Structure of the Roman Brick and
Tile Making in Frankfurt-Nied by Cluster Validation
Jens Dolata, Hans-Joachim Mucha, Hans-Georg Bartel . . . . . . . . . . . . . . . 663
Where Did I See You Before...
A Holistic Method to Compare and Find Archaeological
Artifacts
Vincent Mom. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 671
Keywords . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 681
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 685
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