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Machine Learning and Data Mining in Pattern Recognition

9th International Conference, MLDM 2013, New York, NY, USA, July 19-25, 2013. Proceedings

  • Petra Perner
Conference proceedings MLDM 2013

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7988)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 7988)

Table of contents

  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
  21. Satellite Image Mining for Census Collection: A Comparative Study with Respect to the Ethiopian Hinterland
    Kwankamon Dittakan, Frans Coenen, Rob Christley
    Pages 260-274
  22. Density Ratio Estimation in Support Vector Machine for Better Generalization: Study on Direct Marketing Prediction
    Muhammad Syafiq Mohd Pozi, Aida Mustapha, Anas Daud
    Pages 275-280
  23. Pacc - A Discriminative and Accuracy Correlated Measure for Assessment of Classification Results
    Madhav Sigdel, Ramazan Savas Aygün
    Pages 281-295
  24. A Single-Domain, Representation-Learning Model for Big Data Classification of Network Intrusion
    Shan Suthaharan
    Pages 296-310
  25. Relation Decomposition: The Theory
    Robert Martin Haralick, Ligon Liu, Evan Misshula
    Pages 311-324
  26. Using Turning Point Detection to Obtain Better Regression Trees
    Paul K. Amalaman, Christoph F. Eick, Nouhad Rizk
    Pages 325-339
  27. Automatic Classification of Web Databases Using Domain-Dictionaries
    Heidy M. Marin-Castro, Victor J. Sosa-Sosa, Ivan Lopez-Arevalo, Hugo Jair Escalante-Baldera
    Pages 340-351
  28. An Efficient and Scalable Algorithm for Mining Maximal
    Wael Zakaria Abd Allah, Yasser Kotb El Sayed, Fayed Fayek Mohamed Ghaleb
    Pages 352-366
  29. Partial Discharge Analysis and Inspection Alert Generation in High Power Transformers: A Case Study of an Autotransformer Bank at Eletrobrás-ELETRONORTE Vila do Conde Station
    Carlos Takeshi Kudo Yasojima, Matheus Seribeli Furmigare, Fernando de Souza Brasil, Terezinha Ferreira de Oliveira, Antonio Morais da Silveira
    Pages 367-378
  30. Smart Meter Data Analysis for Power Theft Detection
    Daniel Nikolaev Nikovski, Zhenhua Wang, Alan Esenther, Hongbo Sun, Keisuke Sugiura, Toru Muso et al.
    Pages 379-389
  31. Discovering Frequent Itemsets on Uncertain Data: A Systematic Review
    Juliano Varella de Carvalho, Duncan Dubugras Ruiz
    Pages 390-404
  32. Mining Groups of Common Interest: Discovering Topical Communities with Network Flows
    Liyun Li, Nasir Memon
    Pages 405-420
  33. Optimal Time Segments for Stress Detection
    Nandita Sharma, Tom Gedeon
    Pages 421-433
  34. Personalized Expert-Based Recommender System: Training C-SVM for Personalized Expert Identification
    Yeounoh Chung, Hye-Wuk Jung, Jaekwang Kim, Jee-Hyong Lee
    Pages 434-441
  35. A Comparative Study on Mobile Visual Recognition
    Elisavet Chatzilari, Georgios Liaros, Spiros Nikolopoulos, Yiannis Kompatsiaris
    Pages 442-457
  36. Accuracy-Based Classification EM: Combining Clustering with Prediction
    Stephanie Sapp, Armand Prieditis
    Pages 458-465
  37. When Classification becomes a Problem: Using Branch-and-Bound to Improve Classification Efficiency
    Armand Prieditis, Moontae Lee
    Pages 466-480
  38. Lazy Overfitting Control
    Armand Prieditis, Stephanie Sapp
    Pages 481-491
  39. Using Part of Speech N-Grams for Improving Automatic Speech Recognition of Polish
    Aleksander Pohl, Bartosz Ziółko
    Pages 492-504
  40. An Empirical Study of Reducing Multiclass Classification Methodologies
    R. Kyle Eichelberger, Victor S. Sheng
    Pages 505-519
  41. EEG Feature Selection Based on Time Series Classification
    Michal Vavrečka, Lenka Lhotská
    Pages 520-527
  42. DCA Based Algorithms for Feature Selection in Semi-supervised Support Vector Machines
    Hoai Minh Le, Hoai An Le Thi, Manh Cuong Nguyen
    Pages 528-542
  43. Information Gap Analysis for Decision Support Systems in Evidence-Based Medicine
    Kari Sentz, François M. Hemez
    Pages 543-554
  44. TISA: Topic Independence Scoring Algorithm
    Justin Christopher Martineau, Doreen Cheng, Tim Finin
    Pages 555-570
  45. Pre-release Box-Office Success Prediction for Motion Pictures
    Rohit Parimi, Doina Caragea
    Pages 571-585
  46. Shifting Concepts to Their Associative Concepts via Bridges
    Hongjie Zhai, Makoto Haraguchi, Yoshiaki Okubo, Kiyota Hashimoto, Sachio Hirokawa
    Pages 586-600
  47. Estimating and Forecasting Network Traffic Performance Based on Statistical Patterns Observed in SNMP Data
    Kejia Hu, Alex Sim, Demetris Antoniades, Constantine Dovrolis
    Pages 601-615
  48. A Lightweight Combinatorial Approach for Inferring the Ground Truth from Multiple Annotators
    Xiang Liu, Liyun Li, Nasir Memon
    Pages 616-628
  49. Large Scale Visual Classification with Many Classes
    Thanh-Nghi Doan, Thanh-Nghi Do, François Poulet
    Pages 629-643
  50. Area under the Distance Threshold Curve as an Evaluation Measure for Probabilistic Classifiers
    Sydney Williams, Michael Harris, Jacob Furst, Daniela Raicu
    Pages 644-657

About these proceedings

Introduction

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.

Keywords

algorithms feature selection prediction support vector machines text classification

Editors and affiliations

  • Petra Perner
    • 1
  1. 1.Institute of Computer Vision and Applied Computer Sciences, IBaILeipzigGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-39712-7
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-39711-0
  • Online ISBN 978-3-642-39712-7
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site