Machine Learning and Data Mining in Pattern Recognition

1. Front Matter

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2. The Gapped Spectrum Kernel for Support Vector Machines

   • Taku Onodera, Tetsuo Shibuya

   Pages 1-15

3. Typhoon Damage Scale Forecasting with Self-Organizing Maps Trained by Selective Presentation Learning

   • Kazuhiro Kohara, Isao Sugiyama

   Pages 16-26

4. Dynamic-Radius Species-Conserving Genetic Algorithm for the Financial Forecasting of Dow Jones Index Stocks

   • Michael Scott Brown, Michael J. Pelosi, Henry Dirska

   Pages 27-41

5. Multi Model Transfer Learning with RULES Family

   • Hebah ElGibreen, Mehmet Sabih Aksoy

   Pages 42-56

6. 3D Geovisualisation Techniques Applied in Spatial Data Mining

   • Carlos Roberto Valêncio, Thatiane Kawabata, Camila Alves de Medeiros, Rogéria Cristiane Gratão de Souza, José Márcio Machado

   Pages 57-68

7. Improving the Efficiency of Distributed Data Mining Using an Adjustment Work Flow

   • Jie Gao, Jörg Denzinger

   Pages 69-83

8. Sign Language Recognition with Support Vector Machines and Hidden Conditional Random Fields: Going from Fingerspelling to Natural Articulated Words

   • César Roberto de Souza, Ednaldo Brigante Pizzolato

   Pages 84-98

9. Classification and Outlier Detection Based on Topic Based Pattern Synthesis

   • Samrat Kokkula, Narasimha Murty Musti

   Pages 99-114

10. Decremental Learning of Evolving Fuzzy Inference Systems: Application to Handwritten Gesture Recognition

    • Manuel Bouillon, Eric Anquetil, Abdullah Almaksour

    Pages 115-129

11. Unsupervised Tagging of Spanish Lyrics Dataset Using Clustering

    • Fabio Leonardo Parra, Elizabeth León

    Pages 130-143

12. Feature Learning for Detection and Prediction of Freezing of Gait in Parkinson’s Disease

    • Sinziana Mazilu, Alberto Calatroni, Eran Gazit, Daniel Roggen, Jeffrey M. Hausdorff, Gerhard Tröster

    Pages 144-158

13. Multi-document Text Summarization Using Topic Model and Fuzzy Logic

    • Sanghoon Lee, Saeid Belkasim, Yanqing Zhang

    Pages 159-168

14. A Pattern Based Two-Stage Text Classifier

    • Moch Arif Bijaksana, Yuefeng Li, Abdulmohsen Algarni

    Pages 169-182

15. Applying a Lightweight Iterative Merging Chinese Segmentation in Web Image Annotation

    • Chuen-Min Huang, Yen-Jia Chang

    Pages 183-194

16. Relevance as a Metric for Evaluating Machine Learning Algorithms

    • Aravind Kota Gopalakrishna, Tanir Ozcelebi, Antonio Liotta, Johan J. Lukkien

    Pages 195-208

17. Preceding Rule Induction with Instance Reduction Methods

    • Osama Othman, Christopher H. Bryant

    Pages 209-218

18. Analytic Feature Selection for Support Vector Machines

    • Carly Stambaugh, Hui Yang, Felix Breuer

    Pages 219-233

19. Evaluation of Hyperspectral Image Classification Using Random Forest and Fukunaga-Koontz Transform

    • Semih Dinç, Ramazan Savas Aygün

    Pages 234-245

20. SOM++: Integration of Self-Organizing Map and K-Means++ Algorithms

    • Yunus Dogan, Derya Birant, Alp Kut

    Pages 246-259

This book constitutes the refereed proceedings of the 9th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2013, held in New York, USA in July 2013. The 51 revised full papers presented were carefully reviewed and selected from 212 submissions. The papers cover the topics ranging from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and web mining.

• algorithms
• feature selection
• prediction
• support vector machines
• text classification
• algorithm analysis and problem complexity

• Institute of Computer Vision and Applied Computer Sciences, IBaI, Leipzig, Germany

  Petra Perner

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