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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
  2. Taku Onodera, Tetsuo Shibuya
    Pages 1-15
  3. Hebah ElGibreen, Mehmet Sabih Aksoy
    Pages 42-56
  4. Carlos Roberto Valêncio, Thatiane Kawabata, Camila Alves de Medeiros, Rogéria Cristiane Gratão de Souza, José Márcio Machado
    Pages 57-68
  5. Samrat Kokkula, Narasimha Murty Musti
    Pages 99-114
  6. Fabio Leonardo Parra, Elizabeth León
    Pages 130-143
  7. Sinziana Mazilu, Alberto Calatroni, Eran Gazit, Daniel Roggen, Jeffrey M. Hausdorff, Gerhard Tröster
    Pages 144-158
  8. Sanghoon Lee, Saeid Belkasim, Yanqing Zhang
    Pages 159-168
  9. Moch Arif Bijaksana, Yuefeng Li, Abdulmohsen Algarni
    Pages 169-182
  10. Aravind Kota Gopalakrishna, Tanir Ozcelebi, Antonio Liotta, Johan J. Lukkien
    Pages 195-208
  11. Osama Othman, Christopher H. Bryant
    Pages 209-218
  12. Carly Stambaugh, Hui Yang, Felix Breuer
    Pages 219-233
  13. Yunus Dogan, Derya Birant, Alp Kut
    Pages 246-259
  14. Robert Martin Haralick, Ligon Liu, Evan Misshula
    Pages 311-324
  15. Paul K. Amalaman, Christoph F. Eick, Nouhad Rizk
    Pages 325-339
  16. Heidy M. Marin-Castro, Victor J. Sosa-Sosa, Ivan Lopez-Arevalo, Hugo Jair Escalante-Baldera
    Pages 340-351
  17. Wael Zakaria Abd Allah, Yasser Kotb El Sayed, Fayed Fayek Mohamed Ghaleb
    Pages 352-366
  18. Carlos Takeshi Kudo Yasojima, Matheus Seribeli Furmigare, Fernando de Souza Brasil, Terezinha Ferreira de Oliveira, Antonio Morais da Silveira
    Pages 367-378
  19. Daniel Nikolaev Nikovski, Zhenhua Wang, Alan Esenther, Hongbo Sun, Keisuke Sugiura, Toru Muso et al.
    Pages 379-389
  20. Juliano Varella de Carvalho, Duncan Dubugras Ruiz
    Pages 390-404
  21. Nandita Sharma, Tom Gedeon
    Pages 421-433
  22. Yeounoh Chung, Hye-Wuk Jung, Jaekwang Kim, Jee-Hyong Lee
    Pages 434-441
  23. Elisavet Chatzilari, Georgios Liaros, Spiros Nikolopoulos, Yiannis Kompatsiaris
    Pages 442-457
  24. Stephanie Sapp, Armand Prieditis
    Pages 458-465
  25. Armand Prieditis, Stephanie Sapp
    Pages 481-491
  26. R. Kyle Eichelberger, Victor S. Sheng
    Pages 505-519
  27. Michal Vavrečka, Lenka Lhotská
    Pages 520-527
  28. Hoai Minh Le, Hoai An Le Thi, Manh Cuong Nguyen
    Pages 528-542
  29. Justin Christopher Martineau, Doreen Cheng, Tim Finin
    Pages 555-570
  30. Rohit Parimi, Doina Caragea
    Pages 571-585
  31. Hongjie Zhai, Makoto Haraguchi, Yoshiaki Okubo, Kiyota Hashimoto, Sachio Hirokawa
    Pages 586-600
  32. Kejia Hu, Alex Sim, Demetris Antoniades, Constantine Dovrolis
    Pages 601-615
  33. Thanh-Nghi Doan, Thanh-Nghi Do, François Poulet
    Pages 629-643
  34. 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