4. MLDM 2005: Leipzig, Germany

Classification and Model Estimation

• J. Ko, E. Kim:
  On ECOC as Binary Ensemble Classifiers. 1-10
  
• Anamika Gupta, Naveen Kumar, Vasudha Bhatnagar:
  Incremental Classification Rules Based on Association Rules Using Formal Concept Analysis. 11-20
  
• Yanmin Sun, Andrew K. C. Wong, Yang Wang:
  Parameter Inference of Cost-Sensitive Boosting Algorithms. 21-30
  
• Baibo Zhang, Changshui Zhang:
  Finite Mixture Models with Negative Components. 31-41
  
• Nizar Bouguila, Djemel Ziou:
  MML-Based Approach for Finite Dirichlet Mixture Estimation and Selection. 42-51
  
• Vadim Mottl, Olga Krasotkina, Oleg Seredin, Ilya B. Muchnik:
  Principles of Multi-kernel Data Mining. 52-61
  

Neural Methods

• Ranadhir Ghosh, Moumita Ghosh, John Yearwood, Adil M. Bagirov:
  Comparative Analysis of Genetic Algorithm, Simulated Annealing and Cutting Angle Method for Artificial Neural Networks. 62-70
  
• Ranadhir Ghosh, Moumita Ghosh, John Yearwood, Adil M. Bagirov:
  Determining Regularization Parameters for Derivative Free Neural Learning. 71-79
  
• Johan Huysmans, Bart Baesens, Jan Vanthienen:
  A Comprehensible SOM-Based Scoring System. 80-89
  

Subspace Methods

• Ichigaku Takigawa, Mineichi Kudo, Atsuyoshi Nakamura:
  The Convex Subclass Method: Combinatorial Classifier Based on a Family of Convex Sets. 90-99
  
• Laurent Candillier, Isabelle Tellier, Fabien Torre, Olivier Bousquet:
  SSC: Statistical Subspace Clustering. 100-109
  
• Gero Szepannek, Karsten Luebke, Claus Weihs:
  Understanding Patterns with Different Subspace Classification. 110-119
  

Clustering: Basics

• Christoph F. Eick, Alain Rouhana, Abraham Bagherjeiran, Ricardo Vilalta:
  Using Clustering to Learn Distance Functions for Supervised Similarity Assessment. 120-131
  
• Robert M. Haralick, Rave Harpaz:
  Linear Manifold Clustering. 132-141
  
• Vladimir Nikulin, Alex J. Smola:
  Universal Clustering with Regularization in Probabilistic Space. 142-152
  
• Silke Jänichen, Petra Perner:
  Acquisition of Concept Descriptions by Conceptual Clustering. 153-162
  

Applications of Clustering

• William Sia, Mihai M. Lazarescu:
  Clustering Large Dynamic Datasets Using Exemplar Points. 163-173
  
• Martin Halvey, Mark T. Keane, Barry Smyth:
  Birds of a Feather Surf Together: Using Clustering Methods to Improve Navigation Prediction from Internet Log Files. 174-183
  
• Giorgio Giacinto, Roberto Perdisci, Fabio Roli:
  Alarm Clustering for Intrusion Detection Systems in Computer Networks. 184-193
  
• Eugen Barbu, Pierre Héroux, Sébastien Adam, Éric Trupin:
  Clustering Document Images Using Graph Summaries. 194-202
  

Feature Grouping, Discretization, Selection and Transformation

• Gaëlle Legrand, Nicolas Nicoloyannis:
  Feature Selection Method Using Preferences Aggregation. 203-217
  
• Leon Bobrowski:
  Ranked Modelling with Feature Selection Based on the CPL Criterion Functions. 218-227
  
• Marc Boullé:
  A Grouping Method for Categorical Attributes Having Very Large Number of Values. 228-242
  
• Fabien Scalzo, Justus H. Piater:
  Unsupervised Learning of Visual Feature Hierarchies. 243-252
  
• Sylvain Ferrandiz, Marc Boullé:
  Multivariate Discretization by Recursive Supervised Bipartition of Graph. 253-264
  
• Khaled M. Hammouda, Diego N. Matute, Mohamed S. Kamel:
  CorePhrase: Keyphrase Extraction for Document Clustering. 265-274
  
• EunSang Bak:
  A New Multidimensional Feature Transformation for Linear Classifiers and Its Applications. 275-284
  

Applications in Medicine

• Aristófanes Corrêa Silva, Anselmo Cardoso de Paiva, Alexandre César Muniz de Oliveira:
  Comparison of FLDA, MLP and SVM in Diagnosis of Lung Nodule. 285-294
  
• Aristófanes Corrêa Silva, Valdeci Ribeiro da Silva Jr., Areolino de Almeida Neto, Anselmo Cardoso de Paiva:
  Diagnosis of Lung Nodule Using Reinforcement Learning and Geometric Measures. 295-304
  
• Wenming Cao, Jianhui Hu, Gang Xiao, Shoujue Wang:
  Iris Recognition Algorithm Based on Point Covering of High-Dimensional Space and Neural Network. 305-313
  
• Shuo Li, Thomas Fevens, Adam Krzyzak, Song Li:
  Automatic Clinical Image Segmentation Using Pathological Modelling, PCA and SVM. 314-324
  
• Dimitris A. Karras, Basil G. Mertzios, Danielle Graveron-Demilly, Dirk van Ormondt:
  Improved MRI Mining by Integrating Support Vector Machine Priors in the Bayesian Restoration. 325-333
  
• Lukasz A. Kurgan, Leila Homaeian:
  Prediction of Secondary Protein Structure Content from Primary Sequence Alone - A Feature Selection Based Approach. 334-345
  
• Jun Du, Emin Erkan Korkmaz, Reda Alhajj, Ken Barker:
  Alternative Clustering by Utilizing Multi-objective Genetic Algorithm with Linked-List Based Chromosome Encoding. 346-355
  

Time Series and Sequential Pattern Mining

• Akira Hayashi, Yuko Mizuhara, Nobuo Suematsu:
  Embedding Time Series Data for Classification. 356-365
  
• Horst Bunke, Peter J. Dickinson, Christophe Irniger, Miro Kraetzl:
  Analysis of Time Series of Graphs: Prediction of Node Presence by Means of Decision Tree Learning. 366-375
  
• Kazuhiro Shimizu, Takao Miura:
  Disjunctive Sequential Patterns on Single Data Sequence and Its Anti-monotonicity. 376-383
  
• Keith A. Pray, Carolina Ruiz:
  Mining Expressive Temporal Associations from Complex Data. 384-394
  
• Pierre-Alain Laur, Jean-Emile Symphor, Richard Nock, Pascal Poncelet:
  Statistical Supports for Frequent Itemsets on Data Streams. 395-404
  

Mining Images in Computer Vision

• Klaus-Dieter Kuhnert, Michael Krödel:
  Autonomous Vehicle Steering Based on Evaluative Feedback by Reinforcement Learning. 405-414
  
• Christian Derichs, Frank Deinzer, Heinrich Niemann:
  Cost Integration in Multi-step Viewpoint Selection for Object Recognition. 415-425
  
• J. Y. Lai, Arcot Sowmya, John Trinder:
  Support Vector Machine Experiments for Road Recognition in High Resolution Images. 426-436
  
• Shuyan Zhao, Rolf-Rainer Grigat:
  An Automatic Face Recognition System in the Near Infrared Spectrum. 437-444
  

Mining Images and Texture

• Dmitry Kinoshenko, Vladimir Mashtalir, Elena Yegorova, Vladimir Vinarsky:
  Hierarchical Partitions for Content Image Retrieval from Large-Scale Database. 445-455
  
• Vassili A. Kovalev, Maria Petrou:
  Optimising the Choice of Colours of an Image Database for Dichromats. 456-465
  
• Adeoye I. Adegorite, Otman A. Basir, Mohamed S. Kamel, Khaled Bashir Shaban:
  An Approach to Mining Picture Objects Based on Textual Cues. 466-475
  

Mining Motion from Sequence

• Longin Jan Latecki, Roland Miezianko, Dragoljub Pokrajac:
  Activity and Motion Detection Based on Measuring Texture Change. 476-486
  
• Shiming Xiang, Changshui Zhang, Xiaoping Chen, Naijiang Lu:
  A New Approach to Human Motion Sequence Recognition with Application to Diving Actions. 487-496
  
• Naoya Ohnishi, Atsushi Imiya:
  Dominant Plane Detection Using Optical Flow and Independent Component Analysis. 497-506
  

Speech Analysis

• Halima Bahi, Mokhtar Sellami:
  Neural Expert Model Applied to Phonemes Recognition. 507-515
  
• Cuong Anh Le, Van-Nam Huynh, Akira Shimazu:
  An Evidential Reasoning Approach to Weighted Combination of Classifiers for Word Sense Disambiguation. 516-525
  

Aspects of Data Mining

• Bon K. Sy:
  Signature-Based Approach for Intrusion Detection. 526-536
  
• Tsuyoshi Taniguchi, Makoto Haraguchi, Yoshiaki Okubo:
  Discovery of Hidden Correlations in a Local Transaction Database Based on Differences of Correlations. 537-548
  
• Feiyue Ye, Jiandong Wang, Shiliang Wu, Huiping Chen, Tianqiang Huang, Li Tao:
  An Integrated Approach for Mining Meta-rules. 549-557
  
• Annette Kuhlmann, Ralf-Michael Vetter, Christoph Lübbing, Clemens-August Thole:
  Data Mining on Crash Simulation Data. 558-569
  

Text Mining

• Lee Gillam, Khurshid Ahmad:
  Pattern Mining Across Domain-Specific Text Collections. 570-579
  
• Masoud Makrehchi, Mohamed S. Kamel:
  Text Classification Using Small Number of Features. 580-589
  
• Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen, Dominique Ponson:
  Low-Level Cursive Word Representation Based on Geometric Decomposition. 590-599
  

Special Track: Industrial Applications of Data Mining

• Sylvain Ferrandiz, Marc Boullé:
  Supervised Evaluation of Dataset Partitions: Advantages and Practice. 600-609
  
• Josenildo Costa da Silva, Matthias Klusch:
  Inference on Distributed Data Clustering. 610-619
  
• Lokesh Kumar Sharma, Om Prakash Vyas, Uma Shanker Tiwary, Ranjana Vyas:
  A Novel Approach of Multilevel Positive and Negative Association Rule Mining for Spatial Databases. 620-629
  
• Yinglong Xia, Shifeng Weng, Changshui Zhang, Shao Li:
  Mixture Random Effect Model Based Meta-analysis for Medical Data Mining. 630-640
  
• Shinichi Hamano, Masako Sato:
  Semantic Analysis of Association Rules via Item Response Theory. 641-650
  
• Keshri Verma, Om Prakash Vyas, Ranjana Vyas:
  Temporal Approach to Association Rule Mining Using T-Tree and P-Tree. 651-659
  
• Jong Gyu Han, Kwang Hoon Chi, Yeon Kwang Yeon:
  Aquaculture Feature Extraction from Satellite Image Using Independent Component Analysis. 660-666
  
• Sotiris B. Kotsiantis, George E. Tsekouras, C. Raptis, Panayiotis E. Pintelas:
  Modeling the Organoleptic Properties of Matured Wine Distillates. 667-673
  
• Sotiris B. Kotsiantis, George E. Tsekouras, Panayiotis E. Pintelas:
  Bagging Random Trees for Estimation of Tissue Softness. 674-681
  
• Isabelle Bichindaritz, Sarada Akkineni:
  Concept Mining for Indexing Medical Literature. 682-691
  

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