5. MLDM 2007 Posters: Leipzig, Germany

Petra Perner (Ed.): Machine Learning and Data Mining in Pattern Recognition, 5th International Conference, MLDM 2007, Leipzig, Germany, July 18-20, 2007, Post Proceedings. IBaI publishing 2007, ISBN 978-3-940501-00-4

Text and Document Mining

Euthimios Badekas, Nikos A. Nikolaou, Nikos Papamarkos: Text Localization and Binarization in Complex Color Documents. 1-15
Lazaro S. P. Busagala, Wataru Ohyama, Tetsushi Wakabayashi, Fumitaka Kimura: Integrated Feature Analysis For Automatic Text Classification. 16-26
Jose Ignacio Serrano, Ángel Iglesias, M. Dolores del Castillo: Text Similarity Based on a Cognitive Model of Reading. 27-40
Julien Velcin, Jean-Gabriel Ganascia: A Tabu-based Approach for Topic Extraction. 41-54
Jeong-Hoon Ji, Gyun Woo, Sang-Hyun Park, Hwan-Gue Cho: An Intelligent System for Detecting Source Code Plagiarism Using a Probabilistic Graph Model. 55-69

Image Mining

Zhiwen Yu, Shaohong Zhang, Jiqi Zhang, Hau-San Wong: 3D Head Model Classifcation based on Bayesian classifer. 70-79
Zhiwen Yu, Shaohong Zhang, Jiqi Zhang, Hau-San Wong: 3D Head Model Classifcation based on Cluster Ensemble. 80-89
P. Papadimitriou, Nikos Papamarkos: Color Reduction by Combining Kohonen SOFM and Learning Vector Quantization. 90-104
Fritz Jetzek, Hermann-Josef Kaiser: A Geometric Model of Cytoskeletal Tension in Adherent Cells. 105-119
Jean-Baptiste Bordes, Henri Maître: Semantic Annotation of Satellite Images. 120-133

Network Mining

Chung-Yuan Huang, Chia-Ying Cheng, Chuen-Tsai Sun: Mining Bridge and Brick Network Motifs. 134-143
Yusuf Yaslan, Zehra Cataltepe: A Comparison Framework of Similarity Metrics Used for Web Access Log Analysis. 144-152

Support Vector Machines

Elkin García, Fernando Lozano: Boosting Support Vector Machines. 153-167

Feature Selection, Feature Maps

Terry Windeatt, Matthew Prior, Niv Effron, Nathan Intrator: Ensemble-based Feature Selection Criteria. 168-182
Anjin Park, Keechul Jung: Clustering of Trained Self-organizing Feature Maps based on s-t Graph Cut. 183-195

Prediction and Classfication

Brian Burford: The K29* Algorithm for Linear Prediction. 196-210
Irene M. Cramer, Barbara Rauch, Hagen Fürstenau, Dan Shen, Maria Staudte: Predicting Classifcation Decisions with Data Point Based Meta-learning. 211-215
Davy Sannen, Hendrik Van Brussel, Marnix Nuttin: Classifier Fusion Using Discounted Dempster-Shafer Combination. 216-230
Vladimir A. Fursov, Irina Kulagina, Nikita Kozin: Building of Classifiers Based on Conjugation Indices. 231-235
Ghada Hany Badr: Optimized Similarity Measure Over Trie. 236-150
Indre Zliobaite: Ensemble Learning for Concept Drift Handling - the Role of New Expert. 251-260

Sequence Mining

Trevor Parsons, John Murphy, Patrick O'Sullivan: Applying Frequent Sequence Mining to Identify Design Flaws in Enterprise Software Systems. 261-275
Siyamand Ayubi, Ahmad Baraani-Dastjerdi, Amir Hassan Monadjemi, Maybin K. Muyeba: A Novelty Detection Method Based on Frequent Itemsets. 276-286

Sampling Methods

Jorge de la Calleja, Olac Fuentes: Learning from Imbalanced Datasets using a Distance-based Over-sampling Method. 287-

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